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S3 Fig. Principal component analysis (PCA) identifies genes whose expression is strongly correlated with PCA components 1 and 2. As we matched PCA components 1 and 2 to dor- sal-ventral (D-V) and anterior-posterior (A-P) axes, we looked for the genes best correlated to each component (S4 Table). Color code indicates dissection region identity of the sample according to Fig 1 and S1 Table. (A, B) Neural plate gene sox2.1 expression is correlated to PCA component 1 at both stages, more weakly at stage 12.5 (A, correlation coefficient = −0.86) than at stage 14 (B, correlation coefficient = −0.91). (C, D) Novel gene zc4h2.l expression is even more highly correlated to PCA component 1 at stage 12.5 (C, correlation coefficient = −0.98) and stage 14 (D, correlation coefficient = −0.96). (E, F) Posterior gene cdx2.s presents a high negative correlation with PCA component 2, both at stage 12.5 (E, correlation coefficient = −0.93) and 14 (F, correlation coefficient = −0.95). (G, H) Anterior gene fzd8.s is highly posi- tively correlated with PCA component 2, both at stage 12.5 (G, correlation coefficient = 0.91) and 14 (H, correlation coefficient = 0.88). See S11 Table for numerical data. Image published in: Plouhinec JL et al. (2017) © 2017 Plouhinec et al. This image is reproduced with permission of the journal and the copyright holder. This is an open-access article distributed under the terms of the Creative Commons Attribution license Larger Image Printer Friendly View

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