Determination of the 10% strip for profile extraction along the A–P axis.

<p>The embryo mask (A) is used to calculate the morphological skeleton shown in (B). Along this skeleton we position 5 equidistant points (red dots in C), though which we draw a cubic spline (solid black line in C). This spline is extended to the embryo borders using Lagrange extrapolation. It is then used to determine a band (or strip) that extends 10% along the minor (or dorso-ventral, D–V) axis of the embryo (5% above and below the spline; red lines in C). Expression profiles are extracted from the bright-field image by measuring the average staining intensity of vertical pixel columns that fall within the strip (D).</p

FlyGUI: analysing positional variability.

<p>Screenshot displaying the ‘Analysis: Variability’ tab of our FlyGUI. This tab allows us to plot sets of expression boundaries for specific genes and time classes. Individual slopes and medians can be displayed together (main panel), or separately as median-only (A), or as slopes-only (B) graphs. Either entire gene expression patterns (main panel), or individual slopes (C) can be plotted. Median slopes for multiple genes can be combined (not shown). See text for details.</p

FlyGUI: adding images and creating the embryo mask.

<p>Screenshot displaying the ‘Add Images’ tab of our FlyGUI. This tab is used to create embryo masks from selected DIC images. See text for details.</p

FlyGUI: determining boundary (slope) positions.

<p>Screenshot displaying the ‘Slopes’ tab of our FlyGUI. This tab is used to manually identify the boundaries (slopes) present in extracted expression profiles. In the main screen, the boundaries of <i>kni</i> slope 4 are being positioned. Once satisfactory spline approximations have been found (A), slopes are added to the database by pressing the ‘Slope!’ button. Boundaries may be re-positioned by clicking and dragging on the end knots of the splines (B). Two additional views of the expression profiles aid separation of signal from background by plotting the logarithm (C), or minimum-to-maximum range (D) of the expression profile. Selecting the ‘Channel’ drop-box allows us to switch expression profile view from purple to red stains (E). See text for details.</p

FlyGUI: analysing spatio-temporal dynamics of gene expression.

<p>Screenshot displaying the ‘Analysis: Boundaries’ tab of our FlyGUI. This tab allows us to plot median boundary positions through time to visualise spatio-temporal dynamics of gene expression. See text for details.</p

FlyGUI: editing mask details.

<p>Screenshot displaying the ‘Mask Details’ tab of our FlyGUI. This tab is used for embryo re-orientation, staging, and quality control for the segmentation process. Different embryo images are displayed by clicking on the curved direction arrows (shown in A–E). (A,B) Intermediate images generated after the ‘edge detection’ and ‘fill holes’ operations in the processing pipeline. (C–E) Cropped and rotated DIC, bright-field, and nuclear counterstain images. (F) Pop-out high-resolution image of membrane morphology. See text for details.</p

Generating the embryo mask.

<p>The top row displays the four raw images obtained by microscopy: (A) DIC, (B) bright-field, (C) nuclear counterstain, and (D) detailed membrane morphology. The DIC image is used to create the binary embryo mask. This is achieved through a series of processing steps (1–16), which are described in detail in the Materials and Methods section of the main text.</p

Time classification using FlyAGE.

<p>Screenshot displaying the FlyAge programme, which enables the visualisation of all embryos stained for a particular gene at a particular time class. (A) Drop-down menus at the top of the screen allow the user to select ‘Organism’, ‘Gene’, ‘Time class’, ‘Genotype’ and ‘Knock-down’. Pressing the ‘Load Images’ button displays montages of bright-field images (A), membrane details (B), and nuclear counterstains (C) in separate tabs. (D) Bright-field images, nuclear counterstain, membrane details, and expression slopes (boundaries) can be viewed together in a pop-out window for each individual embryo by clicking on the bright field image. Identified outliers, or misclassified embryos can be reclassified in this window by selecting the correct age from the ‘Time class’ drop-down menu.</p

Image acquisition and processing.

<p>As an example we show quantification of <i>kni</i> expression. (A–D) Embryo images are acquired using wide-field microscopy: unprocessed bright-field (A), DAPI counter-stain (B), and DIC images (C), as well as higher-resolution details of membrane morphology using DIC (D). Whole-embryo DIC images (as shown in C) are subjected to a sequence of image segmentation steps: 1. convert the image to gray-scale, 2. adjust gamma, 3. invert image, 4. apply Sobel edge detection (E), followed by 5. dilation operations, 6. filling of holes, and 7. removal of blobs touching the image border. Only the largest blob is kept, and Gaussian smoothing is applied to generate a binary mask covering the embryo (F). Whole-embryo masks are used to crop bright field (A), DAPI (B) and DIC (C) images, which are then rotated and flipped to orient them anterior to the left and dorsal to the top (G–J). The midline of the embryo is identified by using the skeleton of the whole-embryo mask, which is then approximated by a spline curve for smoothing and pruning of superfluous skeleton branches (K). We establish a band of 10% mask height along the midline of the embryo (K), which is overlain on the bright-field image (H) as shown in (L). A raw expression profile is extracted from this band (M), which shows high and irregular non-specific background. To eliminate this background, profiles are manually annotated and expression boundaries are approximated by cubic spline curves (M). We calculate the median position of extracted boundary positions for each expression profile per time stage and normalise the data (N: boundaries from individual embryos in black, median boundary in red). Median boundaries from multiple time classes are integrated to create an expression profile along the A–P axis though developmental time (O: contour plot with interpolated data between time classes). See main text for details.</p

Comparison of mRNA and protein expression data: gap domain boundary positions.

<p>This table shows mRNA (grey rows) and protein (white rows) boundary locations through developmental time in percent A—P position (where 0% is the anterior pole). A: indicates anterior, P: posterior boundary of a domain. T1—8 indicate time classes subdividing C14A. Boundary positions for mRNA domains correspond to the starting points of approximating splines as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002589#s2" target="_blank">Materials and Methods</a>. Boundary positions for protein domains are taken from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002589#pcbi.1002589-Surkova1" target="_blank">[43]</a>, and correspond to the position where the level of gene expression reaches a threshold of 50% maximum fluorescence intensity. Single dashes indicate boundaries that are not present at a give time point. Double dashes indicate boundaries that are observable, but were not measured in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002589#pcbi.1002589-Surkova1" target="_blank">[43]</a>.</p