11 research outputs found

    Target genes investigated, primer and qPCR information.

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    1<p>Organism from which the gene of interest had originally been isolated.</p>2<p><i>Lolium</i> sp. genes investigated in this work. <i>ALS</i>, Acetolactate synthase; <i>ACCase</i>, Acetyl-coenzyme A carboxylase; <i>CYP</i>: cytochrome P450. Accession numbers are given for the <i>Lolium CYP</i> genes available in GenBank/EMBL that display the highest amino-acid identity with the <i>CYP</i> gene of interest. % identity, % of amino-acid identity between the <i>CYP</i> gene of interest and the <i>Lolium CYP</i> gene studied.</p>3<p>F, forward primer; R, reverse primer.</p

    Ranking of the eight candidate reference genes according to the stability of their expression in samplings IM1 (top) and P1 (bottom) computed using BestKeeper and NormFinder.

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    1<p>Sampling composition given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0063576#pone-0063576-t001" target="_blank">Table 1</a>.</p>2<p>The three reference genes selected are in bold. <i>TUB</i>, beta tubulin; <i>CAP</i>, Capsine phosphatase; <i>EF1</i>, Elongation factor 1; <i>GADPH</i>, Glyceraldehyde 3-phosphate dehydrogenase; <i>RUB</i>, Ribulose-1,5-bisphosphate carboxylase oxygenase; <i>UBQ</i>, Ubiquitin; <i>18S</i>, ribosomal RNA 18S; <i>25S</i>, ribosomal RNA 25S.</p>3<p>Standard deviation of Cq values. SD values higher than the threshold value (1.00) are underlined.</p>4<p>Pearson’s coefficient of correlation.</p>5<p>Stability value.</p>*<p>associated p-value <0.001.</p

    RNA samples used to assess the stability of candidate reference genes (samplings IM1 and P1).

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    1<p>BT, before treatment; xHAT, x hours after treatment.</p>2<p>S, sensitive; R, resistant.</p

    Expression of <i>ALS</i>, <i>ACCase</i> and five <i>CYP</i> genes in individual <i>Lolium</i> sp. plants in four groups of samples.

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    <p>A group of samples consists of the plants from the same population that have been used to assess the effect of the same herbicide in sampling IM2 or P2 (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0063576#pone-0063576-t002" target="_blank">Table 2</a>). For every individual plant, the relative expression levels of each gene measured in the absence of herbicide (BT) and 24 hours after herbicide application (24HAT) are connected by a solid line for herbicide-resistant plants, a dotted line for herbicide-sensitive plants or a dashed-and-dotted line for plants with a moderately resistant phenotype. A given colour in all panels in a column (i.e., in a given group of samples) indicates the same individual plant. Panels on lanes A to G, relative expression levels for <i>ALS</i>, <i>ACCase</i>, <i>CYP71R4</i>, <i>CYP72A</i>, <i>CYP81B1</i>, <i>CYP81A</i> and <i>CYP92A</i>, respectively. The herbicide considered is indicated below the population code using the sampling code (IM2, iodosulfuron+mesosulfuron; P2, pyroxsulam, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0063576#pone-0063576-t002" target="_blank">Table 2</a>). Identical letters in a given panel and in a given experimental modality (BT or 24HAT) indicate relative expression levels that are not significantly different.</p

    Candidate reference genes tested and primer information.

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    1<p><i>TUB</i>, beta tubulin; <i>CAP</i>, Capsine phosphatase; <i>EF1</i>, Elongation factor 1; <i>GADPH</i>, Glyceraldehyde 3-phosphate dehydrogenase; <i>RUB</i>, Ribulose-1,5-bisphosphate carboxylase oxygenase; <i>UBQ</i>, Ubiquitin; <i>18S</i>, ribosomal RNA 18S; <i>25S</i>, ribosomal RNA 25S.</p>2<p>F, forward primer; R, reverse primer.</p>3<p>Values obtained using samplings IM1 or P1 (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0063576#pone-0063576-t001" target="_blank">Table 1</a>).</p>4<p>Average Cq value computed over all samples in samplings IM1 and P1.</p

    geNorm ranking of the eight candidate reference genes according to their average expression stability value M (A) and determination of the optimal number of reference genes for accurate normalisation (B).

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    <p>A, ranking was performed for all RNA samples in samplings IM1 (top) and P1 (bottom). M-values of the remaining genes at each step during stepwise exclusion of the least stable gene are shown. The genes are ranked according to increasing expression stability (i.e., decreasing M-value). B, pairwise variation analysis to determine the optimal number of reference genes for accurate normalisation in samplings IM1 (open boxes) and P1 (solid boxes). The pairwise variation between consecutive normalisation factors (Vi/i+1) indicating the optimal number of reference genes is arrowed.</p

    Number of plants in the samplings used for target gene expression quantification BT and 24HAT (samplings IM2 and P2).

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    1<p>IM2, sprayed with iodosulfuron+mesosulfuron; P2, sprayed with pyroxsulam.</p>2<p>S, sensitive; R, resistant, r, moderately resistant. All plants were analysed before treatment (BT) and 24 hours after treatment (24HAT).</p

    The Impact of a Researcher’s Structural Position on Scientific Performance: An Empirical Analysis

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    <div><p>This article discusses the nature and structure of scientific collaboration as well as the association between academic collaboration networks and scientific productivity. Based on empirical data gathered from the CVs of 73 researchers affiliated with an academic research network in Canada, this study used social network analysis (SNA) to examine the association between researchers’ structural position in the network and their scientific performance. With reference to Granovetter’s and Burt’s theories on weak ties and structural holes, we argue it is the bridging position a researcher holds in a scientific network that matters most to improve scientific performance. The results of correlation scores between network centrality and two different indicators of scientific performance indicate there is a robust association between researchers’ structural position in collaboration networks and their scientific performance. We believe this finding, and the method we have developed, could have implications for the way research networks are managed and researchers are supported.</p></div

    Correlation and simple linear regression coefficients between betweenness centrality and both performance measures (h-index and CPI).

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    <p>Correlation and simple linear regression coefficients between betweenness centrality and both performance measures (h-index and CPI).</p
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