Global scale transcriptome analysis of Arabidopsis embryogenesis in vitro

Background Somatic embryogenesis (SE) in plants is a process by which embryos are generated directly from somatic cells, rather than from the fused products of male and female gametes. Despite the detailed expression analysis of several somatic-to-embryonic marker genes, a comprehensive understanding of SE at a molecular level is still lacking. The present study was designed to generate high resolution transcriptome datasets for early SE providing the way for future research to understand the underlying molecular mechanisms that regulate this process. We sequenced Arabidopsis thaliana somatic embryos collected from three distinct developmental time-points (5, 10 and 15 d after in vitro culture) using the Illumina HiSeq 2000 platform. Results This study yielded a total of 426,001,826 sequence reads mapped to 26,520 genes in the A. thaliana reference genome. Analysis of embryonic cultures after 5 and 10 d showed differential expression of 1,195 genes; these included 778 genes that were more highly expressed after 5 d as compared to 10 d. Moreover, 1,718 genes were differentially expressed in embryonic cultures between 10 and 15 d. Our data also showed at least eight different expression patterns during early SE; the majority of genes are transcriptionally more active in embryos after 5 d. Comparison of transcriptomes derived from somatic embryos and leaf tissues revealed that at least 4,951 genes are transcriptionally more active in embryos than in the leaf; increased expression of genes involved in DNA cytosine methylation and histone deacetylation were noted in embryogenic tissues. In silico expression analysis based on microarray data found that approximately 5% of these genes are transcriptionally more active in somatic embryos than in actively dividing callus and non-dividing leaf tissues. Moreover, this identified 49 genes expressed at a higher level in somatic embryos than in other tissues. This included several genes with unknown function, as well as others related to oxidative and osmotic stress, and auxin signalling. Conclusions The transcriptome information provided here will form the foundation for future research on genetic and epigenetic control of plant embryogenesis at a molecular level. In follow-up studies, these data could be used to construct a regulatory network for SE; the genes more highly expressed in somatic embryos than in vegetative tissues can be considered as potential candidates to validate these networks.

Deforestation, leakage and avoided deforestation policies: a spatial analysis

This paper analyses the impact of several avoided deforestation policies within a patchy forested landscape. Central is the idea that deforestation choices in one area influence deforestation decisions in nearby patches. We explore the interplay between forest landscapes comprising heterogeneous patches, localised spatial displacement, and avoided deforestation policies. Avoided deforestation policies at a landscape level are respectively: two Payments for Environmental Services (PES) policies, one focused on deforestation hotspots, the second being equally available to all agents; a conservation area; and, an agglomeration bonus. We demonstrate how the "best" policy, in terms of reduced leakage, depends on landscape heterogeneity. Agglomeration bonuses are shown to be more effective where there is less landscape heterogeneity, whilst conservation areas are most effective where there is more spatial heterogeneity.

DIAGNOSTIC TECHNIQUES OF LOCAL INFLUENCE IN SPATIAL ANALYSIS OF SOYBEAN YIELD

Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.

A SPATIAL ANALYSIS OF IMPERVIOUS SURFACES AT COLBY COLLEGE IN 1965 AND 2006

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SPATIAL ANALYSIS OF COLBY COLLEGE TRAILS: PERKINS ARBORETUM AND RUNNALS HILL

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Spatial Analysis of Colby College Trails: Perkins Arboretum and Runnals Hill

I created an updated map of trails at Colby College using global positioning system data that were then edited in ArcGIS. The map background, obtained from the Maine Office of GIS, was created from digital orthophotographs produced from aerial photos collected over southwest Maine in Spring 2003. Trail difficulty was determined by creating a slope layer and taking other factors into consideration such as ground surface and path width. The map will eventually be available online, enabling interactive selection of trails where users can access additional trail information.

A Spatial Analysis of Impervious Surfaces at Colby College in 1965 and 2006

Roads, parking lots, buildings, and other impervious surfaces do not allow rainwater to infiltrate the ground. As a result, they can lead to an increase in runoff to nearby ditches and streams, as well as a greater influx of pollutants such as motor oil that can often be found on paved surfaces. For this project, GIS was used to find the total area covered by impervious surfaces on the Colby campus, and to show how this area has grown in the past 40 years. It was found that new development on the campus has lead to a 56% increase in impervious surfaces at Colby since 1965.

Spatial analysis of the distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) and losses in maize crop productivity using geostatistics

A lagarta-do-cartucho, Spodoptera frugiperda (J.E. Smith), é uma das principais pragas do milho nas Américas. O estudo de sua distribuição espacial é fundamental para a utilização de estratégias de controle, otimização de técnicas de amostragens, determinação de danos econômicos e incorporação de um programa de agricultura de precisão. em uma área cultivada com milho foram realizadas amostragens com intervalo semanal, correspondendo ao estádio vegetativo que compreende desde a germinação até o pendoamento. Foram amostradas 10 plantas ao acaso por parcela, no total de 2000 plantas em cada amostragem. A produtividade foi obtida através da colheita de todas as parcelas que eram pesadas separadamente no campo e em cada parcela foram coletadas 15 espigas aleatoriamente para estimar o comprimento e o diâmetro médio. As análises espaciais, utilizando geoestatística, mostraram que o modelo esférico apresentou o melhor ajuste às lagartas pequenas. À medida que as lagartas foram se desenvolvendo sua distribuição foi tornando aleatória, representada por um modelo ajustado por uma reta, não tendo sido detectado nenhum tipo de dependência espacial nos pontos de amostragem. A produtividade e o diâmetro e comprimento da espiga foram descritos por modelos esféricos, indicando uma variabilidade espacial nos parâmetros de produtividade na área cultivada. A geoestatística mostrou-se promissora para a aplicação de métodos precisos no controle integrado de pragas.

Mapping soil pollution by spatial analysis and fuzzy classification

Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.

Identification of Landslide Scars in the Region of the Serra do Mar, São Paulo State, Brazil, Using Digital Image Processing and Spatial Analysis Tools

The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.

Dental caries and the nutritional status of preschool children: a spatial analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evolution and population structure of africanized honey bees in Brazil: Evidence from spatial analysis of morphometric data

In recent years, studies based on isoenzymatic patterns of geographic variation have revealed that what is usually called the Africanized honey bee does not constitute a single population. Instead, several local populations exist with various degrees of admixture with European honey bees. In this paper, we evaluated new data on morphometric patterns of Africanized honey bees collected at 42 localities in Brazil, using univariate and multivariate (canonical) trend surface and spatial autocorrelation analyses. The clinal patterns of variation found for genetically independent characters (wing size characters and some wing venation angles) are concordant with previous studies of malate dehydrogenase (MDH) allelic frequencies and support the hypothesis that larger honey bees in southern and southeastern Brazil originated by racial admixture in the initial phases of African honey bee colonization. Geographic variation patterns of Africanized honey bee populations reflect a demic diffusion process in which European genes were gradually lost because of the higher fitness of the African gene pool in Neotropical environmental conditions.

Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Prevalence of the hepatitis C virus among university employees in São Paulo, southeastern Brazil: predictive factors and geoprocessing spatial analysis

Background There are limited studies on the prevalence and risk factors associated with hepatitis C virus (HCV) infection. Objective Identify the prevalence and risk factors for HCV infection in university employees of the state of São Paulo, Brazil. Methods Digital serological tests for anti-HCV have been performed in 3153 volunteers. For the application of digital testing was necessary to withdraw a drop of blood through a needlestick. The positive cases were performed for genotyping and RNA. Chi-square and Fisher’s exact test were used, with P-value <0.05 indicating statistical significance. Univariate and multivariate logistic regression were also used. Results Prevalence of anti-HCV was 0.7%. The risk factors associated with HCV infection were: age >40 years, blood transfusion, injectable drugs, inhalable drugs (InDU), injectable Gluconergam®, glass syringes, tattoos, hemodialysis and sexual promiscuity. Age (P=0.01, OR 5.6, CI 1.4 to 22.8), InDU (P<0.0001, OR=96.8, CI 24.1 to 388.2), Gluconergam® (P=0.0009, OR=44.4, CI 4.7 to 412.7) and hemodialysis (P=0.0004, OR=90.1, CI 7.5 – 407.1) were independent predictors. Spatial analysis of the prevalence with socioeconomic indices, Gross Domestic Product and Human Development Index by the geoprocessing technique showed no positive correlation. Conclusions The prevalence of HCV infection was 0.7%. The independent risk factors for HCV infection were age, InDU, Gluconergan® and hemodialysis. There was no spatial correlation of HCV prevalence with local economic factors.

Field-scale spatial correlation between contents of iron oxides and CO2 emission in an Oxisol cultivated with sugarcane

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)