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janvier 19371937/01 (N1,PART1,A1937)-1937/01 (N3,PART1,A1937)

Bivariate ETM for flowering time in <i>A. thaliana</i>, for different prediction methods (solid lines) and univariate analysis using observed flowering time, the most correlated environmental variable and the different trait predictions (dotted lines).

<p>Left panel: number of known flowering genes recovered, as a function of total number of genes considered. Right panel: corresponding enrichment probabilities (-log10(p)). The following methods were used: CCA (purple), LM (green), RF (brown), EN (blue), analysis using summer day length and observed flowering time are marked in black and red respectively. Enrichment is defined as the probability of recovering <i>k</i> out of <i>m</i> genes by chance, under the hypergeometric distribution. The area in gray marks the 5% upper and lower percentiles based on 200 permutations of the univariate/bivariate traits.</p

Univariate ETM for flowering time in <i>A. thaliana</i>, for different prediction methods, compared to univariate mapping of summer day length and latitude.

<p>Left panel: number of known flowering genes recovered, as a function of total number of genes considered. Right panel: corresponding enrichment probabilities (-log10(p)). Enrichment is defined as the probability of recovering <i>k</i> out of <i>m</i> genes by chance, under the hypergeometric distribution. Colors represent ETM with CCA prediction (purple), ETM with LM (green), ETM with RF (brown), ETM with EN (blue), univariate mapping of latitude (black), univariate mapping of summer day length (red). Recovery and enrichment based on randomly sampled SNPs are shown as reference (grey dashed line). The area in gray marks the 5% upper and lower percentiles based on 200 permutations of the univariate/bivariate traits.</p

Geographic maps of predicted trait values for the different prediction methods.

<p>Heatmaps showing low to high values of predicted (scaled) flowering time as red (early) to yellow (late).</p

Venn diagram of the top 400 candidate genes.

<p>Left panel: overlap between genes identified by bivariate ETM using the four different prediction methods. Right panel: overlap between univariate association analysis using observed flowering time, bivariate ETM with observed and predicted (LM) flowering time, bivariate ETM with observed flowering time and a randomly simulated variable correlated (<i>r</i> = 0.8) to observed flowering time.</p

Correlation (Pearson <i>r</i>²) with estimated SNP frequency at 4 important flowering loci.

<p>Scatter plots showing (structure corrected) SNP frequencies against predicted flowering time, summer day length and latitude, for 478 accessions without phenotypic observations. In case of predicted flowering time, the prediction method yielding the highest significance is shown for each gene (from top to bottom: RF, CCA, LM, RF). Estimates of SNP frequency were obtained using the program <i>SCAT</i> [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005594#pgen.1005594.ref043" target="_blank">43</a>].</p

Power in simulations.

<p>The proportion of simulated traits for which the -log10(p) value of the causal SNP is above the threshold, for single trait mapping (red), bivariate ETM with the most correlated environmental variable (black), and bivariate ETM with 4 different prediction methods (LM, EN, RF, CCA; respectively green, blue, brown and purple). Bivariate ETM was performed by testing for a common marker effect (left) and by testing whether there is any effect on environment or trait (right). The causal SNP explained 5% of the variance of the simulated trait, while polygenic background and residual variance explained respectively 45% and 50%.</p

Additional file 1: Figures S1-S5 of Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times

and Tables S1-S3. (DOCX 3133 kb

Diagram representing the metapopulation model (a) and example model output (b).

<p>The larger panel in (a) shows six villages with two positive farmers (black crosses) with seed flow indicated by gray arrows. Enlarged area shows a block of nine fields surrounding two fields that received contaminated seed. The field on the left mixed seed from a contaminated source, resulting in a frequency below that of the source field. The field on the right undergoes complete replacement and now has the same transgene frequency as the seed source. Panel (b) presents the spatial distribution of the transgene after 100 generations in the entire metapopulation (top) and in an enlarged area close to the focus of introduction (bottom). Transgene presence is marked in white and frequencies above 0.5 percent in black.</p

Detection probabilities of the transgene for each of the five scenarios.

<p>The observed probabilities refer to the average frequency of trials in which the positive transgene was detected among ten repetitions. Expected probabilities are simple binomial probabilities based on the assumption of spatially homogenous transgene frequencies (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046123#s4" target="_blank">methods</a>).</p