PESTLE Analysis Case Solution

PESTLE Analysis ================ We consider a set of $N$ species, of which each represents a different species of plant. We assume that each species is represented by a $\text{p}$-level model. The aim is to calculate the relative abundances of the different species over the full model, such that the relative abundances of species of minor importance does not have a pathological effect and the impact of “strays” (rare species) is minimized as much as possible.

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In the most simple case, we assume that all plant species occupy a single niche in a specific area and are highly rare. The first case corresponds to the ecological models of Hubbell et al. (1998) whereas the second case is similar to the theoretical models introduced by Lohbeck et al.

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(1998) and Mirebrahimi (1999) as well as to the experimental work of Marland et al. (2000). For experiments in this area, there exists a vast amount of experimental datasets collected under different climate regimes or different crops ([http://data.

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gto-berlin.de](http://data.gto-berlin.

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de/)). These experimental data allow for comparing the relative abundances of both species (species within subcommunity) within a single area under different treatments (e.g.

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soil water content). In all cases the complete set of species are treated as one (i.e.

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the “indicator only” scenario) which is sometimes referred to as “core” analysis or “true ratio” analysis. This allows for obtaining the true value of the plant populations throughout a single area under similar conditions. In our simulations all plant species are treated as being representative for the different plant populations occurring in a single area.

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Thus for all simulations we considered a single area for each soil and for each area both species and the related subcommunity were analysed as if they all “occupy” the same soil niche ([i.e.]{} they all belong to one guild ([e.

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g.]{} we all represent the ground vegetation in our area ([*soil*]{})). Although this is the most simple case, it is unrealistic for evaluating agricultural and land management measures that should have little impact on plant diversity and abundance for long time scales.

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As a result, also “true ratio” analysis seems unrealistic and hence without value for most applications. Model of Plant Populations ========================== The above scenario forces to evaluate plant population models where only the abundance of some species is considered as the predictor and the abundance of the entire plant community is the response. More specifically, we have to predict the distribution of a whole system of plant populations that form a single single system of patches and will be visited by a single pollinator.

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Although the prediction of species and plant population abundance is not possible without a link between the two, the simulation is still a good way of evaluating population dynamics models that aim at predicting the impact of a specific population management measure (such as crop rotation or crop supplementation). For each soil, we considered approximately one hundred patches (for further details see the introduction). Each patch is characterized by a homogeneous matrix in which we represent “empty sites” where there is no plant species ([*empty site*]{}).

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As local conditions vary, the patch is determined by the parameters straight from the source controls how species are distributed accordingly andPESTLE Analysis of the Genome Distribution of Genetically Modified plants Kung-Fai Yu$^{1,2}$, Yu-Chin Wu$^{2}$, Li Yu$^{1}$, Yi-Fang Dai$^{1}$ [$^{1}$[Department of Earth and Planetary Sciences, Peking University, Beijing 100871, China]{}[[email protected]]{}]{} [$^{2}$[Key Laboratory of Life Science, Shenzhen University, Shenzhen, Guangdong 518060, China]{}[[email protected]

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szu.edu.cn]{}]{} ———————————————————————— Pestle toolbox is a data visualization system used for the analysis of genomes and related genotype data.

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It supports various visualization methods such as the generation of a circular visualization of complex data structures such as genomes or genome-centric tables. Besides the visualization of genomic data, PESTLE can generate genome diagrams, including circular representations of circular chromosomes and genomes with their associated chromosomal structures in rectangular boxes. Genomic comparative analyses of closely related species, sequence alignment studies and virus-host disease genome investigations can also be performed on the PESTLE environment.

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PESTLE is provided by the Core Module of PESTLE Package. We mainly present the toolbox with a description of all algorithms for both circular chromosome figures and rectangular box figures with their associated chromosomal structures. For circular chromosome figures, first the required file type (*fda*, *.

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filedata*) is specified, and then *PESTLE*.png is used to produce a circular chromosome representation of the specified file type. For rectangular box figures, a *.

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filedata* file generated by PESTLE Toolbox and displayed with *filedows* application can be read. *filedows* can then generate a rectangular box based on file contents, and then the corresponding chromosomal structure file is visualized with the supplied chromosome labeling file as a rectangular box. The specific commands and syntax in PESTLE are further summarized, and the manual features are also described.

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The toolbox can be used to transform chromosomes and genomic positions into circular chromosome figures for circos plotting. Description of PESTLE ===================== Overview ——– There are many genes located at specific locations on chromosomes. *PESTLE* was designed originally for the analysis of these genes (Genome Tools [@Yu2011]) and is now being used to analyze a wide variety genomic data including genotypes of plants and animals and the genome distribution in both plants and animals [@Yu2011a; @Yu2011b; @Vaccari2013; @Delerive2008; @Casola1998].

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The toolbox is divided into three interactive submodules respectively named as PESTLE View, Genome Graph, and Genome Comparison. As in RNA-Seq, PESTLE Toolbox provides convenient tools for drawing genome diagrams. First, *PESTLE.

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png* and *PESTLE.filedata* can be used to produce a typical circle representing genome positions in particular genomic subregions, and this circle is then put onto a rectangular box for easy genome diagram plotting in *PESTLE* View. Both square and circular chromosomal structures can be drawn onPESTLE Analysis {#S1} ============= Pestle analysis has had an enormous impact on the study of plant materials, ranging from cell walls and enzymes to cells and organs.

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Plants form their secondary metabolites through the enzymatic pathways, which involve a tremendous number of enzymes for the accumulation, differentiation and chemical modification of plant natural products. Therefore, the discovery of the genes is of utmost importance to understand the mechanism of secondary metabolites biosynthesis ([@B64], [@B65]). Hundreds of genes related to secondary compounds have been indentified from the genome of various plants, as well as animals ([@B67]).

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Among them, genes coding for enzymes are most significant. PESTLE in secondary metabolites biosynthesis {#S2} ============================================ The synthesis of secondary metabolites includes the conjugation of sugars with various scaffold compounds like fatty acids, acyl-carotenoids, amino acids, chlorinated chlorogenic acids, etc ([@B17]). This conjugated compounds assemble together into the glycosylated units to form the conjugated pyranocoumarins.

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After the synthesis of these compounds, they are modified in three-dimensional to form the intermediates which are then reduced, yielding the final compounds. While many genes involved in secondary metabolites biosynthesis have been characterized, less attention has been directed toward the genetic determinant of specific compound. The genes for enzymes responsible for the formation of sterols, carotenoids, chlorophyll, and flavonoids are well known in all plant genomes studied (Table [1](#T1){ref-type=”table”}; Supplementary Material).

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Most of the commercially relevant secondary metabolites are produced in vegetative tissues as well as in reproductive organs ([@B68], [@B70]; Table [1](#T1){ref-type=”table”}). Some of the plant secondary metabolites require particular machinery for their biosynthesis through a complex enzymatic route. As plant seeds (especially its endosperm) are the main source of these compounds, the genes of most of the enzymes critical to the biosynthesis of these compounds are often localized in the endosperm of the seeds.

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Genes located in different parts of the plant genome have been shown to participate in the biosynthesis of different classes of metabolites (monoterpenoids, phenylpropanoids, anthraquinones, and volatile compounds). Secondary metabolism in the non-vascular tissues of plants is also characterized by the presence of PESTLE genes. The different tissues and organs of plants are dominated by different secondary metabolites such as steroid hormones, terpenoids, phenylpropanoids, lignins, and volatile compounds.

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More than 50% of the different compounds were found to be formed through the polyketide rings and their derivatives of terpene, phenylpropanoid, and flavonoid biosynthesis. In order to build these compounds, enzymes like aromatases and cytochrome P450s are needed ([@B68], [@B70]). For instance, phenylalanine is derived from octenoyltransferase, aminotransferase, 5-aminovaleroylglutamate transaminase, and cinnamic acid from leucoanthocyanidin reductase ([@B71]).

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###### The class of compounds in which PESTLE

PESTLE Analysis Case Solution
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