Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area (Silos and Smokestacks), in Waterloo, Iowa for the years ended December 31, 2009 and 2008

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area (Silos and Smokestacks), in Waterloo, Iowa for the years ended December 31, 2009 and 2008

State of genomics and epigenomics research in the perspective of HIV cure.

PURPOSE OF REVIEW: One of the seven key scientific priorities identified in the road map on HIV cure research is to 'determine the host mechanisms that control HIV replication in the absence of therapy'. This review summarizes the recent work in genomics and in epigenetic control of viral replication that is relevant for this mission. RECENT FINDINGS: New technologies allow the joint analysis of host and viral transcripts. They identify the patterns of antisense transcription of the viral genome and its role in gene regulation. High-throughput studies facilitate the assessment of integration at the genome scale. Integration site, orientation and host genomic context modulate the transcription and should also be assessed at the level of single cells. The various models of latency in primary cells can be followed using dynamic study designs to acquire transcriptome and proteome data of the process of entry, maintenance and reactivation of latency. Dynamic studies can be applied to the study of transcription factors and chromatin modifications in latency and upon reactivation. SUMMARY: The convergence of primary cell models of latency, new high-throughput quantitative technologies applied to the study of time series and the identification of compounds that reactivate viral transcription bring unprecedented precision to the study of viral latency.

The recent breakthroughs in the understanding of host genomics in hepatitis C.

BACKGROUND: Hepatitis C Virus (HCV) infection is spontaneously resolved in about 30% of acutely infected individuals. In those who progress to chronic hepatitis C, HCV therapy permanently eradicates infection in about 40% of cases. It has long been suspected that host genetic factors are key determinants for the control of HCV infection. DESIGN: We will review in this study four genome-wide association studies (GWAS) and two large candidate gene studies that assessed the role of host genetic variation for the natural and treatment-induced control of HCV infection. RESULTS: The studies consistently identified genetic variation in interleukin 28B (IL28B) as the strongest predictor for the control of HCV infection. Importantly, single nucleotide polymorphisms (SNPs) in IL28B strongly predicted both spontaneous and treatment-induced HCV recovery. IL28B is located on chromosome 19 and encodes interferon-λ, a type III interferon with antiviral activity, which is mediated through the JAK-STAT pathway by inducing interferon-stimulated genes. The SNPs identified in the GWAS are in high linkage disequilibrium with coding or functional non-coding SNPs that might modulate function and/or expression of IL28B. The role of the different IL28B alleles on gene expression and cytokine function has not yet been established. CONCLUSIONS: These findings provide strong genetic evidence for the influence of interferon-λ for both the natural and treatment-induced control of HCV infection, and support the further investigation of interferon-λ for the treatment of chronic hepatitis C. Furthermore, genetic testing before HCV therapy could provide important information towards an individualized HCV treatment.

Plant species richness and environmental heterogeneity in a mountain landscape: effects of variability and spatial configuration

The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area, in Waterloo, Iowa for the years ended December 31, 2010 and 2009

Audit report on America’s Agricultural Industrial Heritage Landscape, Inc., d/b/a Silos and Smokestacks National Heritage Area, in Waterloo, Iowa for the years ended December 31, 2010 and 2009

Médecine génomique et oncologie [Genomics medicine and oncology].

Progress in genomics with, in particular, high throughput next generation sequencing is revolutionizing oncology. The impact of these techniques is seen on the one hand the identification of germline mutations that predispose to a given type of cancer, allowing for a personalized care of patients or healthy carriers and, on the other hand, the characterization of all acquired somatic mutation of the tumor cell, opening the door to personalized treatment targeting the driver oncogenes. In both cases, next generation sequencing techniques allow a global approach whereby the integrality of the genome mutations is analyzed and correlated with the clinical data. The benefits on the quality of care delivered to our patients are extremely impressive.

Genomics and the origin of species.

Speciation is a fundamental evolutionary process, the knowledge of which is crucial for understanding the origins of biodiversity. Genomic approaches are an increasingly important aspect of this research field. We review current understanding of genome-wide effects of accumulating reproductive isolation and of genomic properties that influence the process of speciation. Building on this work, we identify emergent trends and gaps in our understanding, propose new approaches to more fully integrate genomics into speciation research, translate speciation theory into hypotheses that are testable using genomic tools and provide an integrative definition of the field of speciation genomics.

Highlands of the upper Jequitinhonha valley, Brazil: II - mineralogy, micromorphology, and landscape evolution¹

Palm swanp formations, the so-called veredas, typically occur in the Brazilian biome known as "Cerrado" (savanna-like vegetation), especially on flattened areas or tablelands (chapadas). The aim of this study was to characterize the mineralogy and micromorphology of soil materials from a representative toposequence of the watershed of the vereda Lagoa do Leandro, located in Minas Novas, state of Minas Gerais, Brazil, on plains in the region of the upper Jequitinhonha valley, emphasizing essential aspects of their genesis and landscape evolution. The toposequence is underlain by rocks of the Macaúbas group and covered with detrital and metamorphic rocks (schists of Proterozoic diamictites). The soil profiles were first pedologically described; samples of the disturbed and undisturbed soils were collected from all horizons for further micromorphological and mineralogical analyses. The mineralogical analysis was mainly based on powder X ray diffractometry (XRD) and micromorphological descriptions of thin sections under a petrographic microscope. The soils from the bottom to the top of this toposequence were classified as: Typic Albaquult (GXbd), Xanthic Haplustox, gray color, here called "Gray Haplustox" ("LAC"), Xanthic Haplustox (LA) and Typic Haplustox (LVA). The clay mineralogy of all soils was found to be dominated by kaolinite. In soil of LA and LVA, the occurrence of goethite, gibbsite, and anatase was evidenced; "LAC" also contained anatase and the GXbd, illite, anatase, and traces of vermiculite. The micromorphological analyses of the LVA, LA and "LAC" soils showed the prevalence of a microaggregate-like or granular microstructure, and aggregate porosity has a stacked/packed structure, which is typical of Oxisols. A massive structure was observed in GXbd material, with the presence of illuviation cutans of clay minerals and iron compounds. Paleogleissolos, which are strongly weathered, due to the action of the excavating fauna , and resulted in the present "LAC". The GXbd at the base of the vereda preserved the physical, mineralogical and micromorphological properties that are typical of a pedogenesis with a strong influence of long dry periods.

Landscape structure affects dispersal in the greater white-toothed shrew: inference between genetic and simulated ecological distances

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

Magnetic susceptibility to identify landscape segments on a detailed scale in the region of Jaboticabal, São Paulo, Brazil

The agricultural potential is generally assessed and managed based on a one-dimensional vision of the soil profile, however, the increased appreciation of sustainable production has stimulated studies on faster and more accurate evaluation techniques and methods of the agricultural potential on detailed scales. The objective of this study was to investigate the possibility of using soil magnetic susceptibility for the identification of landscape segments on a detailed scale in the region of Jaboticabal, São Paulo State. The studied area has two slope curvatures: linear and concave, subdivided into three landscape segments: upper slope (US, concave), middle slope (MS, linear) and lower slope (LS, linear). In each of these segments, 20 points were randomly sampled from a database with 207 samples forming a regular grid installed in each landscape segment. The soil physical and chemical properties, CO2 emissions (FCO2) and magnetic susceptibility (MS) of the samples were evaluated represented by: magnetic susceptibility of air-dried fine earth (MS ADFE), magnetic susceptibility of the total sand fraction (MS TS) and magnetic susceptibility of the clay fraction (MS Cl) in the 0.00 - 0.15 m layer. The principal component analysis showed that MS is an important property that can be used to identify landscape segments, because the correlation of this property within the first principal component was high. The hierarchical cluster analysis method identified two groups based on the variables selected by principal component analysis; of the six selected variables, three were related to magnetic susceptibility. The landscape segments were differentiated similarly by the principal component analysis and by the cluster analysis using only the properties with higher discriminatory power. The cluster analysis of MS ADFE, MS TS and MS Cl allowed the formation of three groups that agree with the segment division established in the field. The grouping by cluster analysis indicated MS as a tool that could facilitate the identification of landscape segments and enable the mapping of more homogeneous areas at similar locations.

Protein-binding microarrays: probing disease markers at the interface of proteomics and genomics.

DNA-binding proteins mediate a variety of crucial molecular functions, such as transcriptional regulation and chromosome maintenance, replication and repair, which in turn control cell division and differentiation. The roles of these proteins in disease are currently being investigated using microarray-based approaches. However, these assays can be difficult to adapt to routine diagnosis of complex diseases such as cancer. Here, we review promising alternative approaches involving protein-binding microarrays (PBMs) that probe the interaction of proteins from crude cell or tissue extracts with large collections of synthetic or natural DNA sequences. Recent studies have demonstrated the use of these novel PBM approaches to provide rapid and unbiased characterization of DNA-binding proteins as molecular markers of disease, for example cancer progression or infectious diseases.

Fourmidable: a database for ant genomics.

BACKGROUND: Fourmidable is an infrastructure to curate and share the emerging genetic, molecular, and functional genomic data and protocols for ants. DESCRIPTION: The Fourmidable assembly pipeline groups nucleotide sequences into clusters before independently assembling each cluster. Subsequently, assembled sequences are annotated via Interproscan and BLAST against general and insect-specific databases. Gene-specific information can be retrieved using gene identifiers, searching for similar sequences or browsing through inferred Gene Ontology annotations. The database will readily scale as ultra-high throughput sequence data and sequences from additional species become available. CONCLUSION: Fourmidable currently houses EST data from two ant species and microarray gene expression data for one of these. Fourmidable is publicly available at http://fourmidable.unil.ch.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

The Moroccan political partisan landscape : a polarized microcosm?

Using an original investigative protocol and a data base of 4,127 national delegates from ten Moroccan political organizations, surveyed between 2008 and 2012, this article examines the characteristics of party members in Morocco. Initial results indicate that the field of Moroccan political parties is a small world dominated by city dwellers, mature men, and the most highly educated, wealthiest individuals. However, far from being isolated from ordinary citizens, there are social dynamics at work. While it cannot be reduced to a segmented clientele, it is, nonetheless, shaped by an ideal-typical opposition between parties of notables and parties of activists.