Time series of <i>Calanus finmarchicus</i> and the 9 relevant variables identified by the GP procedure.

<p>The time series are ordered from left to right of most frequently occurring. All time series were normalised by dividing each value by the time series maximum value before the GP process.</p

Relevant variables selected by the Genetic Programming based methodology combined with the relevance analysis, the abbreviations used in this article, and the frequency of occurrence of each variable in the 104 approximating functions in the population pool.

<p>The last column indicates the type of relationship between the relevant variables and <i>C</i>. <i>finmarchicus</i>, identified with the gradient analysis.</p

The new conceptual model of potential drivers of <i>Calanus finmarchicus</i> abundance deduced from the GP method supplemented by the relevance and gradient analyses.

<p>The new model is composed of two physical variables, North Atlantic net flow and Sea Surface Temperature, and one biological variable, Herring, which is recognised as a top-down driver.</p

Timeseries used in this study.

<p>The links to the data sets used are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158230#pone.0158230.s003" target="_blank">S3 File</a>.</p

Variables identified as potential drivers of the abundance of <i>C</i>. <i>finmarchicus</i>.

<p>Potential drivers have been sectioned into physical, on the left, and biological, on the right. Biological variables have subsequently been divided into two further groups, top-down and bottom-up, which are positioned above and below <i>C</i>. <i>finmarchicus</i> respectively. The data used in this research article are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158230#pone.0158230.t001" target="_blank">Table 1</a>.</p

Sequences of abrupt shifts in the North Sea.

<p>Time series of <i>C</i>. <i>finmarchicus</i> average annual abundance, with arrows indicating the years of the regime shifts, detected using cumulative sums analysis both on this species and in the 9 variables identified as relevant by GP. The table in the insert specifies the year of the shift and shows its direction: + meaning an increase,—meaning a decrease.</p

MOESM1 of “Noisy beets”: impact of phenotyping errors on genomic predictions for binary traits in Beta vulgaris

Additional file 1: Figure S1. TPR/TNR variability with all SNP and with subsets of 30 or 50 SNP Distribution of TPR (red) and TNR (blue) in the validation set using KNN and RF with all 175 SNP and with subsets of 50 and 30 SNP. TPR and TNR as a function of mislabeled observations, from a 5-fold cross validation repeated 100 times. Results are presented per method

The Role of SwrA, DegU and P_D3 in <i>fla/che</i> Expression in <i>B. subtilis</i>

<div><p>In <i>B. subtilis</i> swarming and robust swimming motility require the positive trigger of SwrA on <i>fla/che</i> operon expression. Despite having an essential and specific activity, how SwrA executes this task has remained elusive thus far. We demonstrate here that SwrA acts at the main σ^A-dependent <i>fla/che</i> promoter P_{A(<i>fla/che</i>)} through DegU. Electrophoretic mobility shift assays (EMSA) reveal that SwrA forms a complex with the phosphorylated form of DegU (DegU~P) at P_{A(<i>fla/che</i>)} while it is unable to do so with either unphosphorylated DegU or the DegU32(Hy) mutant protein. Motility assays show that a highly phosphorylated DegU is not detrimental for flagellar motility provided that SwrA is present; however, DegU~P represses P_{A(<i>fla/che</i>)} in the absence of SwrA. Overall, our data support a model in which DegU~P is a dual regulator, acting either as a repressor when alone or as a positive regulator of P_{A(<i>fla/che</i>)} when combined with SwrA. Finally, we demonstrate that the σ^D-dependent P_{D3(<i>fla/che</i>)} promoter plays an important role in motility, representing a contingent feedback loop necessary to maintain basal motility when <i>swrA</i> is switched to the non-functional <i>swrA</i>^- status. </p> </div

The contribution of P_D3(fla/che) to motility is masked by SwrA.

<p>The effect of a P_D3(fla/che) deletion on motility was evaluated in strains differing in the status of the <i>swrA</i> allele or of the σ^D-dependent <i>swrA</i> promoter. The isogenic strains used are PB5392 [<i>swrA</i>⁺ P_D3(fla/che)wt], PB5455 [<i>swrA</i>⁺ ΔP_D3(fla/che)], PB5394 [P_<i>swrA</i>D^--<i>swrA</i>⁺ P_D3(fla/che)wt], PB5458 [P_<i>swrA</i>D^--<i>swrA</i>⁺ ΔP_D3(fla/che)], PB5396 [<i>swrA</i>^- P_D3(fla/che)wt] and PB5466 [<i>swrA</i>^- ΔP_D3(fla/che)]. (<b>A</b>) Swimming assays. Genotypes are indicated on the left and on top of each panel. (<b>B</b>) Swimming expansion measurements. Relevant genotypes are specified on the right. Results shown are an average of three independent experiments; error bars correspond to standard deviation. (<b>C</b>) Western blot of flagellin collected at T₁ from liquid cultures of the strains used in A and B, vertically aligned to the bullets identifying the strains in B. (<b>D</b>) Swimming assay for a Δ<i>sigD </i><i>swrA</i>⁺ strain (PB5427) shown as reference for non-motile behavior.</p

Motility defects caused by the <i>swrA</i>^- and <i>degU32</i>(Hy) alleles are suppressed by an optimized P_A(fla/che).

<p>In the A and B panels swimming (left) and swarming (right) performances of <i>swrA</i>^- or <i>swrA</i>^-<i>degU32</i>(Hy) strains containing the <i>dhsA6</i> mutation is respectively shown. The single nucleotide <i>dhsA6</i> mutation in P_A(fla/che) improves similarity to the σ^A consensus sequence [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085065#B16" target="_blank">16</a>] and thus the predicted promoter strength. Motility of the parental <i>swrA</i>^- and <i>swrA</i>^-<i>degU32</i>(Hy) strains is shown in C and D respectively. Relevant genotypes are indicated on top of each panel. Strains used to generate the images are: PB5452 (A); PB5447 (B); PB5370 (C); PB5384 (D). </p