RAD-QTL mapping reveals both genome-level parallelism and different genetic architecture underlying the evolution of body shape in Lake Whitefish (Coregonus clupeaformis) species pairs

Parallel changes in body shape may evolve in response to similar environmental conditions, but whether such parallel phenotypic changes share a common genetic basis is still debated. The goal of this study was to assess whether parallel phenotypic changes could be explained by genetic parallelism, multiple genetic routes, or both. We first provide evidence for parallelism in fish shape by using geometric morphometrics among 300 fish representing five species pairs of Lake Whitefish. Using a genetic map comprising 3438 restriction site-associated DNA sequencing single-nucleotide polymorphisms, we then identified quantitative trait loci underlying body shape traits in a backcross family reared in the laboratory. A total of 138 body shape quantitative trait loci were identified in this cross, thus revealing a highly polygenic architecture of body shape in Lake Whitefish. Third, we tested for evidence of genetic parallelism among independent wild populations using both a single-locus method (outlier analysis) and a polygenic approach (analysis of covariation among markers). The single-locus approach provided limited evidence for genetic parallelism. However, the polygenic analysis revealed genetic parallelism for three of the five lakes, which differed from the two other lakes. These results provide evidence for both genetic parallelism and multiple genetic routes underlying parallel phenotypic evolution in fish shape among populations occupying similar ecological niches.Keywords : Adaptive radiation, Parallel evolution, Fish body shape, Geometric morphometrics, Genotyping-by-sequencing

A review of the quantification and classification of pigmented skin lesions: from dedicated to hand-held devices

In recent years, the incidence of skin cancer caseshas risen, worldwide, mainly due to the prolonged exposure toharmful ultraviolet radiation. Concurrently, the computerassistedmedical diagnosis of skin cancer has undergone majoradvances, through an improvement in the instrument and detectiontechnology, and the development of algorithms to processthe information. Moreover, because there has been anincreased need to store medical data, for monitoring, comparativeand assisted-learning purposes, algorithms for data processingand storage have also become more efficient in handlingthe increase of data. In addition, the potential use ofcommon mobile devices to register high-resolution imagesof skin lesions has also fueled the need to create real-timeprocessing algorithms that may provide a likelihood for thedevelopment of malignancy. This last possibility allows evennon-specialists to monitor and follow-up suspected skin cancercases. In this review, we present the major steps in the preprocessing,processing and post-processing of skin lesion images,with a particular emphasis on the quantification andclassification of pigmented skin lesions. We further reviewand outline the future challenges for the creation of minimum-feature,automated and real-time algorithms for the detectionof skin cancer from images acquired via common mobiledevices

3D City Model Generation Using Aerial Ortho-Rectified Imagery and LIDAR Data Fusion in Semi-Automatic Way

One of the most interesting research topics in the last decade is generating 3 Dimensions (3D) city model, nevertheless representing a suitable method to achieve the required rapid, automatic, accurate extraction of realistic model for large urban area used for GIS applications and photogrammetry is still a challenging issue. Consequently, a new technique and strategy that increase the efficiency for the 3D city modeling is required. The aim of this research is to develop a simple and efficient semi-automatic approach to generate a 3D city model for urban area using the fusion of LiDAR data and Ortho-rectified imagery. This integration of these data sources provides its efficiency for 3D building extraction that represents the main item in the 3D city model. This approach use both LiDAR data and imagery as the primary cue to delineate building outlines, based on pixel based classification. The third dimension is obtained automatically from normalized digital surface model nDSM, and then the 3D model is generated using multi-Faceted patch The accuracy assessment for both height and building outlines is conducted using the referring to the ground truth. The results of the accuracy assessment stage illustrated by means of the well-known statistical methods.  It is experimentally validated that the proposed approach can successfully detect different types of buildings from simple rectangle to circular –shape, when assessed in terms of different quantitative statistics criteria and visual inspection

Population genomic analysis of North American eastern wolves (Canic lycaon) support their conservation priority status

The threatened eastern wolf is found predominantly in protected areas of central Ontario and has an evolutionary history obscured by interbreeding with coyotes and gray wolves, which challenges its conservation status and subsequent management. Here, we used a population genomics approach to uncover spatial patterns of variation in 281 canids in central Ontario and the Great Lakes region. This represents the first genome-wide single nucleotide polymorphism (SNP) dataset with substantial sample sizes of representative populations. Although they comprise their own genetic cluster, we found evidence of eastern wolf dispersal outside of the boundaries of protected areas, in that the frequency of eastern wolf genetic variation decreases with increasing distance from provincial parks. We detected eastern wolf alleles in admixed coyotes along the northeastern regions of Lake Huron and Lake Ontario. Our analyses confirm the unique genomic composition of eastern wolves, which are mostly restricted to small fragmented patches of protected habitat in central Ontario. We hope this work will encourage an innovative discussion regarding a plan for managed introgression, which could conserve eastern wolf genetic material in any genome regardless of their potential mosaic ancestry composition and the habitats that promote them

Scientific challenges and present capabilities in underwater robotic vehicle design and navigation for oceanographic exploration under-ice.

This paper reviews the scientific motivation and challenges, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. Scientific needs for routine access under fixed and moving ice by underwater robotic vehicles are reviewed in the contexts of geology and geophysics, biology, sea ice and climate, ice shelves, and seafloor mapping. The challenges of under-ice vehicle design and navigation are summarized. The paper reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed glacial or sea ice and moving sea ice). © 2020 by the authors

Genetics and Genomics of Forest Trees

Forest tree genetics and genomics are advancing at an accelerated rate, thanks to recent developments in high-throughput, next-generation sequencing capabilities, and novel biostatistical tools. Population and landscape genetics and genomics have seen the rise of new approaches implemented in large-scale studies that employ the use of genome-wide sampling. Such studies have started to discern the dynamics of neutral and adaptive variation in nature and the processes that underlie spatially explicit patterns of genetic and genomic variation in nature. The continuous development of genetic maps in forest trees and the expansion of QTL and association mapping approaches contribute to the unravelling of the genotype-phenotype relationship and lead to marker-assisted and genome-wide selection. However, major challenges lie ahead. Recent literature suggests that species demography and genetic diversity have been affected both by climatic oscillations and anthropogenically induced stresses in a way calls into question the possibility of future adaptation. Moreover, the pace of contemporary environmental change presents a great challenge to forest tree populations and their ability to adapt, taking into consideration their life history characteristics. Several questions emerge that include, but are not limited to, the interpretation of forest tree genome surveillance and their structural/functional properties, the adaptive and neutral processes that have shaped forest tree genomes, the analysis of phenotypic traits relevant to adaptation (especially adaptation under contemporary climate change), the link between epigenetics/epigenomics and phenotype/genotype, and the use of genetics/genomics as well as genetic monitoring to advance conservation priorities

Design and optimization of 2.5 dimension porous media micromodel for nanosensor flow experiments

Micromodels are used to visualize and study pore-scale phenomena such as immiscible displacements in porous media, foam flow behavior, and CO2 flooding. The understanding gained from these experiments can be used to develop models to predict future behavior of the reservoir. Most micromodels are constructed using lithography techniques that are restricted to 2D patterns that require artificial generation or manipulation of images to develop connected micromodels. Characteristics innate to the original rock structure are often lost or skewed in developing micromodels that bear little resemblance to the original media. Alternative microfabrication techniques using a micromilling tool have allowed us to vary the floor height in a micromodel, thus giving some variation in the third dimension. We refer to these structures (with varying floor height and fixed ceiling, and which cannot have passages on top of one another) as 2.5D micromodels. Using a technique called depth averaging, in which we take a section of a 3D voxel image of porous media and project the solid voxels down while simultaneously pushing the void space above, we generate micromodels that may allow for more accurate representations of the pore structure in 3D rock. The design of the etched pattern requires the selection of a specific depth (or number of XMCT image slice) over which to average the image data. The 2.5-D pattern was obtained by optimizing a series of parameters to ensure the structure and flow patterns matched as closely as possible to the equivalent 3D structure and flow as can be accommodated given the restricted dimensionality. Parameters considered include flow-based parameters, common statistical correlations, and a host of topological parameters obtained by network model generation techniques. For a Boise sandstone core sample imaged at 5.07 µm/pixel, an optimized depth of 115 µm gave the most accurate measures across the range of parameters. However, due to constraints regarding the resolution of the micromilling process, a second series of flow simulations were conducted in the originally optimized region of interest (100-150 µm) for a lower resolution image that resulted in the selection of 130 µm to depth average. This design was then used to fabricate a brass mold insert. The process of developing the microchips for nanosensor experiments is currently in the stage of assembling the PMMA chips

Morphologic Instability of Graphene and its Potential Applications

Graphene is a monolayer of graphite. The surge of interest in graphene, as epitomized by the Nobel Prize in Physics in 2010, is largely attributed to its exceptional properties. Ultra thin, mechanically tough, electrically conductive, and transparent graphene films promise to enable a wealth of possible applications ranging from thin-film solar cells, flexible displays, to biochemical sensing arrays. However, significant gaps remain to realize these potential applications, largely due to the difficulty of precisely controlling graphene properties. Graphene is intrinsically non-flat and tends to be randomly corrugated. The random graphene morphology can lead to unstable performance of graphene devices as the corrugating physics of graphene is closely tied to its electronic properties. Future success of graphene-based applications hinges upon precise control of the graphene morphology, a significant challenge largely unexplored so far. This dissertation aims to explore viable pathways to tailoring graphene morphology and leverage possible morphologic instability of graphene for novel nano-device applications. Inspired by recent experiments, we propose and benchmark a strategy to precisely control the graphene morphology via extrinsic regulation (e.g., substrate surface features, patterned nanowires and nanoparticles). A general energetic framework is delineated to quantitatively determine the extrinsically regulated graphene morphology through energy minimization. Such a framework is benchmarked by determining the graphene morphology regulated by various types and dimensions of nanoscale extrinsic scafffolds, including two dimensional herringbone and checkerboard corrugations on substrate surfaces and one dimensional substrate surface grooves and patterned nanowires. The results reveal a snap-through instability of the graphene morphology, that is, depending on interfacial bonding energy and substrate surface roughness, the graphene morphology exhibits a sharp transition between two distinct states: (1) closely conforming to the substrate surface and (2) remaining nearly flat on the substrate surface. This snap-through instability of graphene holds potential to enable graphene-based functional nano-devices (e.g., ultrasensitive nano-switches). Another type of morphologic instability of graphene is the spontaneous scrolling of graphene into a carbon nanoscroll (CNS). The spiral multilayer nanostructure of CNSs is topologically open and thus distinct from that of carbon nanotubes (CNTs). The unique topological structure of CNSs can enable an array of novel applications, e.g., hydrogen storage, water channels and ultrafast nano-oscillators. However, the realization of CNS-based applications is hindered by the lack of reliable approach to fabricating high quality CNSs. We propose a simple physical approach to fabricating CNSs via CNT-initiated scrolling of graphene on a substrate. The successful formation of a CNS depends on the CNT diameter, the carbon-carbon interaction strength and the graphene-substrate interaction strength. We further demonstrate that the resulting CNS/CNT nanostructure can be used as an ultrafast axial nano-oscillator that operates at 10s GHz. Such CNS-based nano-oscillators can be excited and driven by an external AC electric field, further illustrating their potential to enable nano-scale energy transduction, harnessing and storage

Uncovering of intraspecies macular heterogeneity in cynomolgus monkeys using hybrid machine learning optical coherence tomography image segmentation

The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea and is now being considered as an accompanying imaging method in drug development, such as antivascular endothelial growth factor and its safety profiling. Because animal numbers are limited in preclinical studies and automatized image evaluation tools have not yet been routinely employed, essential reference data describing the morphologic variations in macular thickness in laboratory cynomolgus monkeys are sparse to nonexistent. A hybrid machine learning algorithm was applied for automated OCT image processing and measurements of central retina thickness and surface area values. Morphological variations and the effects of sex and geographical origin were determined. Based on our findings, the fovea parameters are specific to the geographic origin. Despite morphological similarities among cynomolgus monkeys, considerable variations in the foveolar contour, even within the same species but from different geographic origins, were found. The results of the reference database show that not only the entire retinal thickness, but also the macular subfields, should be considered when designing preclinical studies and in the interpretation of foveal data