Genomic determinants of the efficiency of internal ribosomal entry sites of viral and cellular origin

Variation in cellular gene expression levels has been shown to be inherited. Expression is controlled at transcriptional and post-transcriptional levels. Internal ribosome entry sites (IRES) are used by viruses to bypass inhibition of cap-dependent translation, and by eukaryotic cells to control translation under conditions when protein synthesis is inhibited. We aimed at identifying genomic determinants of variability in IRES-mediated translation of viral [Encephalomyocarditis virus (EMCV)] and cellular IRES [X-linked inhibitor-of-apoptosis (XIAP) and c-myc]. Bicistronic lentiviral constructs expressing two fluorescent reporters were used to transduce laboratory and B lymphoblastoid cell lines [15 CEPH pedigrees (n = 205) and 50 unrelated individuals]. IRES efficiency varied according to cell type and among individuals. Control of IRES activity has a significant genetic component (h2 of 0.47 and 0.36 for EMCV and XIAP, respectively). Quantitative linkage analysis identified a suggestive locus (LOD 2.35) on chromosome 18q21.2, and genome-wide association analysis revealed of a cluster of SNPs on chromosome 3, intronic to the FHIT gene, marginally associated (P = 5.9E-7) with XIAP IRES function. This study illustrates the in vitro generation of intermediate phenotypes by using cell lines for the evaluation of genetic determinants of control of elements such as IRE

Opening the black box of outer space: the case of Jason-3

If you look at a rendering of planet Earth from a bird's eye view, you will see satellites orbiting the planet like electrons, each one a testament to humanity's expansion beyond Earth's atmosphere. It begs the question: what is this new humanized landscape? The dominant voice that has attempted to answer this question is the realist one, which has led the charge of academic inquiry into outer space since the fateful launch of the Sputnik in 1957. Though enlightening in some respects, the realist perspective oftentimes obscures the heterogeneous complexity of the actors, actions, limits and possibilities that have constructed this very humanized outer space. This paper looks at the humanization of outer space through the lens of JASON-3, an internationally collaborative satellite designed primarily to measure the topography of the Earth's oceans. A vast number of actors collaborated to enact the network that created JASON-3, including bureaucratic agencies, academics, private contractors, political bodies, other satellites, the sun and even gravity. This paper will focus on these actors and the work that they did to form the network, showing a glimpse of the entangled connections that eventually produced JASON-3. Through telling this story, I argue: (1) outer space is more complex than state-level relations and (2) critical geography -- with its insight into relational spaces and deconstructing power structures -- has a unique place to fill in outer space literature

Determining leaf area index and leafy tree roughness using terrestrial laser scanning

Vegetation roughness, and more specifically forest roughness, is a necessary component in better defining flood dynamics both in the sense of changes in river catchment characteristics and the dynamics of forest changes and management. Extracting roughness parameters from riparian forests can be a complicated process involving different components for different required scales and flow depths. For flow depths that enter a forest canopy, roughness at both the woody branch and foliage level is necessary. This study attempts to extract roughness for this leafy component using a relatively new remote sensing technique in the form of terrestrial laser scanning. Terrestrial laser scanning is used in this study due to its ability to obtain millions of points within relatively small forest stands. This form of lidar can be used to determine the gaps present in foliaged canopies in order to determine the leaf area index. The leaf area index can then be directly input into resistance equations to determine the flow resistance at different flow depths. Leaf area indices created using ground scanning are compared in this study to indices calculated using simple regression equations. The dominant riparian forests investigated in this study are planted and natural poplar forests over a lowland section of the Garonne River in Southern France. Final foliage roughness values were added to woody branch roughness from a previous study, resulting in total planted riparian forest roughness values of around Manning's n = 0.170–0.195 and around n = 0.245–330 for in-canopy flow of 6 and 8 m, respectively, and around n = 0.590 and around n = 0.750 for a natural forest stand at the same flow depths

A Comparative Study between Two Regression Methods on LiDAR Data: A Case Study

Airborne LiDAR (Light Detection and Ranging) has become an excellent tool for accurately assessing vegetation characteristics in forest environments. Previous studies showed empirical relationships between LiDAR and field-measured biophysical variables. Multiple linear regression (MLR) with stepwise feature selection is the most common method for building estimation models. Although this technique has provided very interesting results, many other data mining techniques may be applied. The overall goal of this study is to compare different methodologies for assessing biomass fractions at stand level using airborne Li- DAR data in forest settings. In order to choose the best methodology, a comparison between two different feature selection techniques (stepwise selection vs. genetic-based selection) is presented. In addition, classical MLR is also compared with regression trees (M5P). The results when each methodology is applied to estimate stand biomass fractions from an area of northern Spain show that genetically-selected M5P obtains the best results

Assessing drivers of intra-seasonal grassland dynamics in a Kenyan savannah using digital repeat photography

Understanding grassland dynamics and their relationship to weather and grazing is critical for pastoralists whose livelihoods depend on grassland productivity. Studies investigating the impacts of climate and human factors on inter-seasonal grassland dynamics have focused mostly on changes to vegetation structure. Yet, quantifying the impact of these on the inter-seasonal dynamics of specific grassland communities is not known. This study uses digital repeat photography to examine how intra-seasonal grassland dynamics of different grassland communities are affected by precipitation, temperature, and grazing in a heterogeneous semi-arid savannah in Kenya. A low-cost digital repeat camera network allowed for fine-scale temporal and spatial variability analysis of grassland dynamics and grazing intensity. Over all grass communities, our results show precipitation driving mainly early-season and in some cases mid-season flushing, temperature driving end-of-season senescence, and grazing influencing mid-season declines. Yet, our study quantifies how these three drivers do not uniformly impact grassland species communities. Specifically, Cynodon and Cynodon/Bothriochloa communities are rapidly and positively associated with precipitation, where mid-season declines in Cynodon communities are associated with grazing and late-season declines in Cynodon/Bothriochloa communities are associated with temperature increases. Setaria communities, on the other hand, have weaker associations with the drivers, with limited positive associations with precipitation and grazing. Kunthii/Digitaria diverse communities had no association with the three drivers. Highly diverse mixed communities were associated with increased precipitation and temperature, as well as lower intensity grazing. Our research sheds light on the complex interactions between plants, animals, and weather. Furthermore, this study also demonstrates the potential of digital repeated photography to inform about fine-scale spatial and temporal patterns of semi-arid grassland vegetation and grazing, with the goal of assisting in the formulations of management practises that better capture the intra-annual variability of highly heterogeneous dryland systems

Mapping Opuntia stricta in the arid and semi-arid environment of Kenya using sentinel-2 imagery and ensemble machine learning classifiers

Globally, grassland biomes form one of the largest terrestrial covers and present critical social–ecological benefits. In Kenya, Arid and Semi-arid Lands (ASAL) occupy 80% of the landscape and are critical for the livelihoods of millions of pastoralists. However, they have been invaded by Invasive Plant Species (IPS) thereby compromising their ecosystem functionality. Opuntia stricta, a well-known IPS, has invaded the ASAL in Kenya and poses a threat to pastoralism, leading to livestock mortality and land degradation. Thus, identification and detailed estimation of its cover is essential for drawing an effective management strategy. The study aimed at utilizing the Sentinel-2 multispectral sensor to detect Opuntia stricta in a heterogeneous ASAL in Laikipia County, using ensemble machine learning classifiers. To illustrate the potential of Sentinel-2, the detection of Opuntia stricta was based on only the spectral bands as well as in combination with vegetation and topographic indices using Extreme Gradient Boost (XGBoost) and Random Forest (RF) classifiers to detect the abundance. Study results showed that the overall accuracies of Sentinel 2 spectral bands were 80% and 84.4%, while that of combined spectral bands, vegetation, and topographic indices was 89.2% and 92.4% for XGBoost and RF classifiers, respectively. The inclusion of topographic indices that enhance characterization of biological processes, and vegetation indices that minimize the influence of soil and the effects of atmosphere, contributed by improving the accuracy of the classification. Qualitatively, Opuntia stricta spatially was found along river banks, flood plains, and near settlements but limited in forested areas. Our results demonstrated the potential of Sentinel-2 multispectral sensors to effectively detect and map Opuntia stricta in a complex heterogeneous ASAL, which can support conservation and rangeland management policies that aim to map and list threatened areas, and conserve the biodiversity and productivity of rangeland ecosystems

Genome-wide associations of gene expression variation in humans

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level

Factor VIII gene inversions causing severe hemophilia A originate almost exclusively in male germ cells

The factor VIII gene, which is defective In hemophilia A, is located in the last megabase of the long arm of the X chromosome. Inversions due to intrachromosomal homologous recombination between mispaired copies of gene A located within intron 22 of the gene and about 500 kb telomeric to it account for nearly half of all cases of severe hemophilia A. We hypothesized that pairing of Xq with its homolog inhibits the Inversion process, and that, therefore, the event originates predominantly in male germ cells. In all 20 informative cases In which the inversion originated in a maternal grandparent, DNA polymorphism analysis determined that it occurred in the male germline. In addition, all but one of 50 mothers of sporadic cases due to an Inversion were carriers. Thus, these data support the hypothesis and Indicate that factor VIII gene inversions leading to severe hemophilia A occur almost exclusively In male germ cell

Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells

The fraction of experimentally active conserved non-coding sequences within any given cell type is low, so classical assays are unlikely to expose their potential