Telescoper: de novo assembly of highly repetitive regions.

MotivationWith advances in sequencing technology, it has become faster and cheaper to obtain short-read data from which to assemble genomes. Although there has been considerable progress in the field of genome assembly, producing high-quality de novo assemblies from short-reads remains challenging, primarily because of the complex repeat structures found in the genomes of most higher organisms. The telomeric regions of many genomes are particularly difficult to assemble, though much could be gained from the study of these regions, as their evolution has not been fully characterized and they have been linked to aging.ResultsIn this article, we tackle the problem of assembling highly repetitive regions by developing a novel algorithm that iteratively extends long paths through a series of read-overlap graphs and evaluates them based on a statistical framework. Our algorithm, Telescoper, uses short- and long-insert libraries in an integrated way throughout the assembly process. Results on real and simulated data demonstrate that our approach can effectively resolve much of the complex repeat structures found in the telomeres of yeast genomes, especially when longer long-insert libraries are used.AvailabilityTelescoper is publicly available for download at sourceforge.net/p/[email protected] informationSupplementary data are available at Bioinformatics online

Decoding coalescent hidden Markov models in linear time

In many areas of computational biology, hidden Markov models (HMMs) have been used to model local genomic features. In particular, coalescent HMMs have been used to infer ancient population sizes, migration rates, divergence times, and other parameters such as mutation and recombination rates. As more loci, sequences, and hidden states are added to the model, however, the runtime of coalescent HMMs can quickly become prohibitive. Here we present a new algorithm for reducing the runtime of coalescent HMMs from quadratic in the number of hidden time states to linear, without making any additional approximations. Our algorithm can be incorporated into various coalescent HMMs, including the popular method PSMC for inferring variable effective population sizes. Here we implement this algorithm to speed up our demographic inference method diCal, which is equivalent to PSMC when applied to a sample of two haplotypes. We demonstrate that the linear-time method can reconstruct a population size change history more accurately than the quadratic-time method, given similar computation resources. We also apply the method to data from the 1000 Genomes project, inferring a high-resolution history of size changes in the European population.Comment: 18 pages, 5 figures. To appear in the Proceedings of the 18th Annual International Conference on Research in Computational Molecular Biology (RECOMB 2014). The final publication is available at link.springer.co

Deep Learning for Population Genetic Inference

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statis- tics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Inter- estingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme

Structural Design of a Geodesic-inspired Structure for Oculus: Solar Decathlon Africa 2019

The goal of this project was to create the structural design for a lightweight dome frame structure for the 2019 Solar Decathlon Africa competition in Morocco. The design consisted of developing member sizes and joint connections using both wood and steel. In order to create an innovative and competitive design we incorporated local construction materials and Moroccan architectural features. The result was a structure that would be a model for geodesic inspired homes that are adaptable and incorporate sustainable features

Influence of Fatigue and Anticipation on Knee Kinematics and Kinetics during a Jump-cut Maneuver

BACKGROUND AND PURPOSE: Injuries to the anterior cruciate ligament (ACL) are common among athletes, particularly females. This research aims to reconcile the anticipated and unanticipated movement pattern of jumping and cutting with fatigue for both genders. The research will compare lower extremity biomechanics of a jump-cut after a sports specific fatigue protocol, intending to examine movement patterns which may predispose the subject to ACL injury. METHODS: Twenty healthy subjects were studied (24.9±3.3yrs), including 10 females. A 3D electromagnetic system measured knee kinematics and kinetics during jump-cut tasks. The jump-cut task included anticipated (A) and unanticipated (UA) trials to both directions. For the UA trials, the subject was unaware of the cutting direction until initiation of the task. The fatigue protocol consisted of jumping, sprinting, step-ups, and agility. Subjects completed the jump-cut task again in a fatigued state. A repeated measures ANOVA was used to analyze peak and mean angles, moments and ground reaction forces (GRF), with post-hoc Tukey tests for significant findings between factors (gender, pre/post-fatigue, A/UA). RESULTS: Significant main effects were found for gender and IR/ER and ADD/ABD peak and/or mean angles, and ADD/ABD moments; pre and post-fatigue and IR/ER, EXT/FLEX, and ADD/ABD peak and/or mean angles, and ADD/ABD moments; A/UA conditions and IR/ER and ADD/ABD peak and/or mean angles. Significant interactions existed for gender and A/UA for EXT moment and for pre/post-fatigue and A/UA for EXT moment, IR moment and IR/ER angles. CONCLUSION: Subjects demonstrated significant changes in knee kinematics and kinetics. Fatigue and A/UA states influenced knee movement patterns in variable ways, which may indicate an attempt to safely land and cut. Additionally, females demonstrated biomechanics that may increase their risk for ACL injury relative to males. Gender, fatigue, and A/UA conditions had an impact on one another and should be considered when designing sports training programs to reduce risky movement patterns

Yeast genomic expression patterns in response to low-shear modeled microgravity

The low-shear microgravity environment, modeled by rotating suspension culture bioreactors called high aspect ratio vessels (HARVs), allows investigation in ground-based studies of the effects of microgravity on eukaryotic cells and provides insights into the impact of space flight on cellular physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) causes significant phenotypic changes of a select group of Saccharomyces cerevisiae genes associated with the establishment of cell polarity, bipolar budding, and cell separation. However, the mechanisms cells utilize to sense and respond to microgravity and the fundamental gene expression changes that occur are largely unknown. In this study, we examined the global transcriptional response of yeast cells grown under LSMMG conditions using DNA microarray analysis in order to determine if exposure to LSMMG results in changes in gene expression. LSMMG differentially changed the expression of a significant number of genes (1372) when yeast cells were cultured for either five generations or twenty-five generations in HARVs, as compared to cells grown under identical conditions in normal gravity. We identified genes in cell wall integrity signaling pathways containing MAP kinase cascades that may provide clues to novel physiological responses of eukaryotic cells to the external stress of a low-shear modeled microgravity environment. A comparison of the microgravity response to other environmental stress response (ESR) genes showed that 26% of the genes that respond significantly to LSMMG are involved in a general environmental stress response, while 74% of the genes may represent a unique transcriptional response to microgravity. In addition, we found changes in genes involved in budding, cell polarity establishment, and cell separation that validate our hypothesis that phenotypic changes observed in cells grown in microgravity are reflected in genome-wide changes. This study documents a considerable response to yeast cell growth in low-shear modeled microgravity that is evident, at least in part, by changes in gene expression. Notably, we identified genes that are involved in cell signaling pathways that allow cells to detect environmental changes, to respond within the cell, and to change accordingly, as well as genes of unknown function that may have a unique transcriptional response to microgravity. We also uncovered significant changes in the expression of many genes involved in cell polarization and bud formation that correlate well with the phenotypic effects observed in yeast cells when grown under similar conditions. These results are noteworthy as they have implications for human space flight

Twisting arms and sending messages: Terrorist tactics in civil war

We examine the strategic rationale for terrorist tactics in civil war. We identify conditions that favor terrorism as a tactic in armed civil conflicts as well as the specific targets as a function of rebel characteristics, goals, and government responses to political demands. Terrorist tactics can be helpful as an instrument to coerce the government in asymmetric conflicts, as rebels are typically weak relative to the government. But terrorism can also help communicate the goals and resolve of a group when there is widespread uncertainty. We consider the strategic importance and rationale for terrorism in terms of the frequency of attacks and specific targets, and analyze our propositions using new data linking actors from the Uppsala/PRIO Armed Conflict Data and the Global Terrorism Database. Consistent with our expectations, we find that terrorism is used more extensively in civil conflicts by weaker groups and when attacks can help the group convey its goals without undermining popular support. Groups with more inclusive audiences are more likely to focus on ‘hard’ or official targets, while groups with more sectarian audiences are more likely to attack ‘soft’ targets and civilians

Soft Templating and Disorder in an Applied 1D Cobalt Coordination Polymer Electrocatalyst

Disordered materials with resilient and soft-templated functional units bear the potential to fill the pipeline of robust catalysts for renewable energy storage. However, for novel materials lacking long-range order, the ability to discern local structure with atomic resolution still pushes the boundaries of current analytical and modeling approaches. We introduce a two-pillar strategy to monitor the formation and unravel the structure of the first disordered onedimensional cobalt coordination polymer catalyst, Co-dppeO2. This target material excels through proven high performance in commercial alkaline electrolyzers and organic transformations. We demonstrate that the key architecture behind this activity is the unconventional embedding of hydrated {H2O-Co2(OH)2-OH2} edge-site motifs, nested into a flexible organic matrix of highly oxidized and bridging hydrophobic dppeO2 ligands. Our combination of in situ spectroscopy and computational modeling of X-ray scattering and absorption spectra, backed with complementary experimental techniques, holds the key to understanding the atomic-range structure of important disordered materials

The Story of Here: A Graphic Guide to Holy Cross and College Hill

This illustrated guide captures the history of the section of Worcester where the College of the Holy Cross is located. Historical sources and imaginative interpretations based on historical research are combined to create a unique then and now approach and experience of double vision to tell the story of College Hill. This guide was a project of Montserrat Seminar 111N, taught by Prof. Sarah Luria in Spring 2020.https://crossworks.holycross.edu/hc_books/1051/thumbnail.jp