Name: Quantifying Abdominal Pigmentation in Drosophila melanogaster (Video) | JoVE Journal
Uploaded: 2017-06-01T12:30:00.000+00:00
Duration: 8 min 41 s
Description: Learn to quantify abdominal pigmentation in Drosophila melanogaster using digital image analysis. This non-destructive method enables precise measurement of pigmentation spread and depth for evolutionary biology research.

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This work was funded by National Science Foundation grants IOS-1256565 and IOS-1557638 to AWS. We thank Patricia Wittkopp and three anonymous reviewers for their helpful comments on an earlier version of this paper.

1. Specimen Mounting
NOTE: Store dead flies in 70% ethanol in water prior to imaging.
<ol>
	<li>Pour 10 mL of 1.25% agar dissolved in boiling water in a 60 mm x 15 mm Petri dish and allow it to set.</li>
	<li>Under a dissecting microscope, use a pair of fine-point forceps to make a ~20 mm ong, 2 mm wide, 1 mm deep groove in the surface of the gel. Using fine forceps, embed the ventral side of an adult fly in the groove, with the dorsal side of the fly projecting above the gel. 
	NOTE: The looseness of the gel allows for easy repositioning without damaging the specimen. The same groove can be used for multiple specimens, although it will become dirty, broken-up, and unusable with time. The user can then make another groove in the same gel. Each plate can be used to image ~200 flies.</li>
	<li>Completely cover the specimen in 70% ethanol in water to reduce any light reflections from the waxy cuticle and to prevent wing damage during specimen manipulation.</li>
</ol>
2. Microscope Setup
NOTE: Images are acquired using a dissecting scope, transmitted light base, digital camera, and gooseneck cold light source attached to a computer running image acquisition control software. Software instructions are specific to Micro-Manager v1.4.2044, which is an open-source software that incorporates ImageJ45.
<ol>
	<li>Turn on the microscope, digital camera, double gooseneck cold light source, and computer.</li>
	<li>Run the image capture software to open a Micro-Manager window and an ImageJ window. In the ImageJ window click &#34;Image&#34; &#62; &#34;Type&#34; &#62; &#34;8-Bit&#34; to set all images as 8-bit. Click &#34;live&#34; in the Micro-Manager window to open a &#34;Snap/Live&#34; window showing a real-time preview from the camera.
	<ol>
		<li>Maximize the size of the &#34;Snap/Live&#34; window if necessary. Select &#34;Grayscale&#34; in the pulldown &#34;Display mode&#34; menu in the &#34;Contrast&#34; tab of the Micro-Manager window.</li>
	</ol>
	</li>
	<li>Turn on the cold light source to its maximum intensity and position the tips of each gooseneck to approximately 120 mm from the stage, one on the left and one on the right. 
	NOTE: Users can also use an annular illuminator, although this may generate a ring of reflected light around the fly abdomen.</li>
	<li>Manually set the microscope magnification to 60X so that the field of view captures an area approximately 3 mm in diameter on the stage.</li>
	<li>Place a 2 mm stage micrometer on the stage (switching the background to white if necessary). While looking at the live preview, focus on the stage micrometer and adjust the exposure in the Micro-Manager window by entering the exposure time in ms in the &#34;Exposure&#34; box.</li>
	<li>To spatially calibrate the camera, select the &#34;straight line&#34; tool in the ImageJ window and draw a line the length of the stage micrometer. In the ImageJ window click &#34;Analyze&#34; &#62; &#34;Set Scale&#34; to open the &#34;Set Scale&#34; window, enter the length of the micrometer in &#181;m in the &#34;Known distance&#34; box, and enter &#34;&#181;m&#34; in the &#34;Unit of length&#34; box.
	<ol>
		<li>See that the &#34;Set Scale&#34; window then displays the scale in &#34;pixels/&#181;m.&#34; Make a note of the scale and click &#34;OK.&#34;</li>
	</ol>
	</li>
	<li>In the &#34;Snap/Live&#34; window, click &#34;Stop&#34; and then &#34;Snap&#34; to capture an image of the stage micrometer.</li>
	<li>Save the image as an 8-bit grayscale TIFF to ensure the ability to spatially calibrate the images again if necessary. In the ImageJ window click &#34;File&#34; &#62; &#34;Save As&#34; &#62; &#34;Tiff&#8230;&#34; Specify where to save the file in the file browser, name the file, and click &#34;Save.&#34;</li>
	<li>Switch the stage to black and place a Petri dish holding a fly mounted in agar (steps 1.1-1.2) on the stage.</li>
	<li>Look through the microscope and position the fly to ensure that the dorsal midline is straight up in order to best view the pigmentation pattern. Move any wings and appendages to ensure that the view of the abdomen is unobstructed. If the pigmented cuticle (a2-a5) is not visible, squeeze the abdomen laterally until it is (although the abdomen of flies stored in 70% ethanol in water stretch, so that this is not usually necessary). 
	NOTE: When positioning the fly, the user may need to use a lower magnification (20X). The magnification must be returned to 60X before proceeding.</li>
	<li>Manually focus on the dorsal abdomen of the fly. Manually adjust the tips of the light source to minimize the shadows and reflection on the dorsal abdomen.</li>
	<li>While looking at the live preview on the computer screen, and using the pixel value histogram in the &#34;Contrast&#34; tab of the Micro-Manager window, adjust the exposure as described in step 2.4 to maximize the range of pixel values of the preview image.</li>
	<li>Remove the fly and Petri dish and replace them with an LED (spectral output of 430-660 nm) connected to a voltage meter, centered in the field of view at the same position as the fly. Use the LED and voltage meter as a light meter46 and record the voltage generated by the light striking the LED (~125 mV). 
	NOTE: The LED and voltage meter are used to ensure that light levels are constant across multiple imaging sessions within a single experiment.</li>
	<li>For the duration of the experiment, do not further change the position or intensity of the light source, the magnification of the microscope, or the exposure of the camera.</li>
</ol>
3. Specimen Imaging
<ol>
	<li>Place a Petri dish holding a fly mounted in agar (steps 1.1-1.3) on the black microscope stage.Adjust the position of the fly so that the third and fourth abdominal segments are visible and the dorsal midline is straight up, as described in step 2.9. Ensure that the magnification is at 60x before proceeding.</li>
	<li>Manually focus the microscope such that the third and fourth dorsal abdominal tergites are in focus. Use the image capture software to acquire an image as an 8-bit grayscale TIFF, as described in step 2.6. 
	NOTE: The image can be captured in color and subsequently converted to grayscale for analysis.</li>
	<li>Save the image as &#34;SESH000_sampleID.tiff,&#34; as described in step 2.7. 
	NOTE: Here, [SESH] is constant, [000] is the session number and is variable but must be three digits long, and [sampleID] is whatever the user wishes, although it must not contain any additional underscore (_) characters and must be of a constant length. [sampleID] should include details of the factors used in the analysis of the pigmentation data (e.g., temperature or lineage), separated by a distinctive non-alphabetical character, such as a hyphen (-). This allows these factors to be easily parsed out of [sampleID] using standard statistical software.</li>
	<li>Remove the Petri dish from the stage and replace the fly with the next specimen. Repeat steps 3.1-3.3 until all the specimens have been imaged, without further adjusting the lighting levels, magnification, or exposure.</li>
</ol>
4. Imaging Across Multiple Sessions
<ol>
	<li>If images need to be taken over multiple sessions, maintain the light intensity, exposure, and magnification across sessions. At the beginning of each session, check the spatial calibration of the camera (step 2.4) and the light intensity at the stage (as measured by the LED/voltage meter, step 2.12).</li>
	<li>Capture and save an image of the stage micrometer (steps 2.5-2.7) to ensure the ability to spatially calibrate the images again, if necessary.</li>
	<li>Use at least 15 control specimens and randomly re-image them in each session to allow for the detection and elimination of session effects. Ensure that duplicate control specimens between sessions have the same [sampleID] but different [SESH000]. 
	NOTE: The control specimens are flies collected, stored, and mounted identically to experimental specimens but are re-imaged across sessions. The precise number of control specimens will depend on the user&#39;s experimental setup. See the discussion for further details.</li>
</ol>
5. Image Analysis
NOTE: Image analysis is conducted in ImageJ45 and uses the &#34;Measurement of Pigmentation.ijm,&#34; macro provided as a supplementary file.
<ol>
	<li>Place all images to be analyzed in the same folder.</li>
	<li>Start ImageJ and run the &#34;Measurement of Pigmentation.ijm&#34; macro by clicking &#34;Plugins&#34; &#62; &#34;Macro&#34; &#62; &#34;Run,&#34; selecting &#34;Measurement of Pigmentation.ijm&#34; in the file browser, and clicking &#34;open.&#34; 
	NOTE: All subsequent steps are within the macro. Each step is an individual macro command.</li>
	<li>Note that an &#34;Action Required&#34; dialog box opens, stating &#34;Choose the folder where images are stored.&#34; Click &#34;OK&#34; and use the file browser to select the folder containing the images and then click &#34;choose.&#34;</li>
	<li>Note that an &#34;Action Required&#34; dialog will box open, stating &#34;Choose the folder where you want the data to be stored.&#34; Click &#34;OK&#34; and use the file browser to select the desired folder for saving the pigmentation profiles. Click &#34;choose.&#34;</li>
	<li>Note that a dialog box will open, asking &#34;How many characters in your sample ID?&#34; In the data input box, enter the number of characters in [SampleID], as specified in step 3.3, and click &#34;OK.&#34;</li>
	<li>Note that a dialog box will open, asking &#34;How wide is your ROI?&#34; In the data input box, enter the pixel width of the anterior-posterior strip along which the pigmentation profile is to be read (green rectangle, Figure 1G, Figure 2A, and 2A&#39;). Click &#34;OK;&#34; the default is 20 pixels. 
	NOTE: The pigmentation profile is read across a strip of cuticle, rather than a line, to reduce noise due to hairs and bristles. The width of this strip will depend on the resolution of the image, but it should be ~1/20th of the width of the abdomen, in pixels.</li>
	<li>Note that the macro will open the image of the first fly, and a dialog box will ask whether to measure the current fly (click &#34;Yes&#34;), to go on to the next fly (click &#34;No&#34;), or to exit the macro (click &#34;Cancel&#34;).</li>
	<li>Note that a dialog box will open, stating &#34;Define the midline of the dorsal abdomen, from ANTERIOR to POSTERIOR.&#34; The &#34;straight line&#34; tool will already be selected. Draw a line from anterior to posterior to define the midline of the dorsal abdomen. Click &#34;OK;&#34; see Figure 2A and 2A&#39;, yellow line. 
	NOTE: This is used to reorient the image so that the dorsal midline lies horizontally across the screen, with the anterior on the left, making the subsequent steps easier.</li>
	<li>Note that a dialog box will open, stating &#34;Define the POSTERIOR edge of Tergite 4 just behind the pigment band.&#34; The &#34;straight line&#34; tool will already be selected. Draw a line from the posterior midline edge to the right-lateral edge, such that the center of the line (marked by a white square) sits just posteriorly to the posterior edge of the pigment band (cuticle a5). Click &#34;OK;&#34;. See Figure 2A and 2A&#8242;, magenta line. 
	NOTE: The R script will automatically detect the posterior edge of the pigment band from the pigmentation profile.</li>
	<li>Note that a dialog box will open, stating &#34;Define the ANTERIOR edge of Tergite 4 at the anterior edge of the pigmented cuticle (a2).&#34; The &#34;straight line&#34; tool will already be selected. Draw a line from the anterior midline edge to the right-lateral edge, such that the center of the line (marked by a white square) sits at the anterior edge of the pigmented cuticle (cuticle a2). Click &#34;OK;&#34;. See Figure 2A and 2A&#39;, cyan line. 
	NOTE: The R script will define this point as the anterior edge of the pigmented cuticle of the tergite. On the image, the macro will show the region of interest (ROI) along which the pigmentation profile is read (green rectangle, Figure 2A and 2A&#8242;, enlarged in Figure 2B and 2B&#8242;). The macro will also open a second window showing the pigmentation profile for the ROI (Figure 2C and 2C&#8242;), where the x-axis is the position, expressed as the number of pixels from the posterior edge of the profile, and the y-axis is the average pixel value at each position.</li>
	<li>View the plots of the pigmentation profile that will be opened by the macro. If necessary, click &#34;Live&#34; in the profile window to adjust the position of the ROI so that it does not include any structures (e.g., bristles) that would influence the pigmentation profile. Once the profile is satisfactory, click &#34;OK.&#34;</li>
	<li>Repeat steps 5.8-5.11 for Tergite 3. 
	NOTE: The macro then exports the pigmentation profiles as two CSV files, each named &#34;SESH000_samplename_TX_profile.csv,&#34; where [SESH000_samplename] is the image name and [TX] is either T3 or T4 for the third and fourth tergites, respectively.</li>
	<li>Note that the macro opens the next image. Repeat steps 5.7-5.13 until all images have been analyzed.</li>
</ol>
6. Data Preprocessing, Analysis, and Session Correction
NOTE: All data analysis is conducted in R47 and uses the &#34;Analysis of Pigmentation.R&#34; script provided. Below, &#34;L&#8230;&#34; indicates which line(s) of the script to run for each part of the analysis. See the Supplementary Information for additional details on how the analysis is conducted.
<ol>
	<li>Edit the R script to set the working directory (L6) and define the filepath to the folder containing the.csv profiles (L11).</li>
	<li>Run L13-15 to generate a list of the pigmentation profiles stored in the profile folder.</li>
	<li>Load and run the &#34;reader&#34; and &#34;addPrimaryKey&#34; functions (L17-41) to read the profiles into a single data frame.</li>
	<li>Edit the script at L43 to specify the spatial calibration of the images in &#181;m/pixels, as determined in step 2.5.</li>
	<li>Load and run the &#34;adjustments&#34; function (L46-58) to convert the profile position (x-axis, Figure 2C and 2C&#8242;) from pixels-from-posterior-edge-of-ROI to &#181;m-from-anterior-edge-of-ROI and the profile value (y-axis, Figure 2C and 2C&#8242;) from the pixel value (0 = black, 255 = white) to the pigmentation value (0 = no pigment, 255 = maximum pigment).</li>
	<li>Load and run the &#34;spline.der.er&#34; function (L60-71) to generate the cubic spline of the pigmentation profiles and its first and second derivatives (Figure 2D-2F and 2D&#8242;-2F&#8242;).</li>
	<li>Load and run the &#34;coord&#34; and &#34;assmbly.coord&#34; functions (L74-163), first to extract the position of the posterior (T3) and anterior (T2) edges of the pigment band (Figure 2D and 2D&#8242;) and the posterior edge of the a2 cuticle (T1, Figure 2D and 2D&#8242;), and then to extract the maximum (Pmax) and minimum (Pmin) pigmentation values, taken at T3 and T1, respectively. 
	NOTE: The anterior edge of the a2 cuticle has already been defined in step 5.9.</li>
	<li>Optional: Load and run the &#34;chek&#34; function (L165-175) to check whether the &#34;coord&#34; function is correctly identifying positions T1-3 for a randomly selected pigmentation profile.</li>
	<li>Load and run the index and metrics functions (L178-193) to generate a data table with the headings &#34;Session,&#34; &#34;Sample,&#34; &#34;Tergite,&#34; &#34;id&#34; (a concatenation of Sample and Tergite), &#34;Pmax,&#34; &#34;Pmin,&#34; &#34;Wband&#34;(width of the pigment band, = T3 - T2), and &#34;Wtergite&#34;(width of the pigmented cuticles a2-a5, = T3).</li>
	<li>Load and run the &#34;correction&#34; function (L196-234) to generate a data table that corrects Pmax and Pmin for any nuisance factors arising due to session effects. Use the average increase (or decrease) in Pmax or Pmin from the control specimens re-imaged across temporally adjacent sessions.</li>
</ol>

The authors have nothing to disclose.

This methodology allows for the precise, rapid, and repeatable acquisition of pigmentation data in a quantitative form suitable for multiple downstream analyses. The method has been used to acquire data on the effect of temperature on abdominal pigmentation in an isogenic line of flies. However, the methodology could be used in forward-genetics studies to identify genes that underlie pigmentation differences between individuals, populations, or species, or reverse-genetic studies to explore the effects of specific genes ...

Pigmentation shows enormous phenotypic variation between species, populations, and individuals, and even within individuals during ontogeny1,2,3,4,5,6. Although there are myriad studies of pigmentation in a wide variety of animals, pigmentation has perhaps been best studied in Drosophila melanogaster, where the full power of molecular genetics has been used to elucidate the developmental and physiological mechanisms that regulate pigmentation and how these mechanisms evolve1,6. Much is known about the genes that regulate the biochemical synthesis of pigments in D. melanogaster7,8 and the genes that control the temporal and spatial distribution of this biosynthesis9,10,11,12,13. Furthermore, genetic mapping has identified the genetic loci underlying intra- and interspecific differences in pigmentation in D. melanogaster14,15,16,17. The relationships between pigmentation and pleiotropic traits, such as behavior18,19 and immunity19,20, have also been explored, as has the adaptive significance of pigmentation patterns15,21,22. As such, pigmentation in D. melanogaster has emerged as a powerful yet simple model for the development and evolution of complex phenotypes.
Pigmentation in adult D. melanogaster is characterized by distinct patterns of melanization across the body, particularly on the wings and dorsal thorax and abdomen. It is the pigmentation of each cuticular plate (tergite) on the dorsal abdomen, however, that has received the most research attention. There is considerable variation in this pigmentation (Figure 1A-F), because of both genetic17,23 and environmental24,25 factors. The cuticle of an abdominal tergite is made up of anterior and posterior developmental compartments (Figure 1G), each of which can be further subdivided depending based on pigmentation and ornamentation26. The anterior compartment includes six cuticle types (a1-a6), and the posterior compartment includes three (p1-p3) (Figure 1G). Of these, the p1, p2, and a1 cuticle are typically folded under the tergite in un-stretched abdomens so that they are hidden. The reliably visible cuticle is characterized by a band of heavy pigmentation, here referred to as a &#34;pigment band,&#34; comprised of cuticle types a4 (hairy with moderate bristles) and a5 (hairy with large bristles), with the posterior edge of the band more intensely pigmented than the anterior edge (Figure 1G). Anterior to this band is a region of lightly pigmented hairy cuticle, which has bristles posteriorly (a3) but not anteriorly (a2). Variation in pigmentation between flies is observed in both the intensity of pigmentation and in the width of the pigment band. In general, variation is greatest in the most posterior segments (abdominal segments 5, 6, and 7) and is lower in the more anterior segments (abdominal segments 3 and 4)24. Furthermore, there is a sexual dimorphism in D. melanogaster pigmentation, with males generally having wholly pigmented fifth and sixth abdominal tergites (Figure 4C).
In most studies of abdominal pigmentation in D. melanogaster, pigmentation has been treated as a categorical or ordinal trait, with the pattern measured qualitatively27,28,29 or semi-quantitatively on a scale14,15,16,17,24,30,31,32,33,34,35,36,37. These methods inevitably suffer from a lack of precision, and because they rely on the subjective assessment of pigmentation, it is difficult to compare the data across studies. Several authors have quantified the spatial dimensions of pigmentation38,39, the intensity of pigmentation of a particular cuticle type23,25,39,40, or the average intensity of pigmentation across the abdominal tergite as a whole41,42,43. Nevertheless, these quantification methods do not measure both the intensity and the spatial distribution of abdominal pigmentation simultaneously and therefore do not capture the nuances of how pigmentation varies across the abdominal tergite. Furthermore, several of these quantification methods38,41,42,43 require the dissection and mounting of the abdominal cuticle. This is both time consuming and destroys the sample, making it unavailable for additional morphological analyses. As the understanding of the development and evolution of abdominal pigmentation deepens, more sophisticated tools to quickly and precisely measure both the spatial distribution and the intensity of pigmentation will be required.
The overall goal of this method is to utilize digital image analysis to obtain a replicable and more precise measure of the abdominal pigmentation in D. melanogaster. The methodology includes three stages. First, the adult fly is non-destructively mounted, and a digital image of the dorsal abdomen is taken. Second, using an ImageJ macro, the user defines an anterior-posterior strip of pixels that extends from the anterior of the a2 cuticle to the posterior of the a5 cuticle (green box, Figure 1G) on both the third and fourth abdominal segments. The average pixel value across the width of this strip is then extracted along its long axis, generating a profile that captures the spatial distribution and intensity of pigmentation as it changes from the anterior to the posterior of the tergite. Third, an R script is used to describe the pigmentation profile mathematically using a cubic spline. The R script then uses the spline and its first and second derivative to extract the width of the a2-a5 cuticle, the width of the pigment band, and the maximum and minimum levels of pigmentation. The method therefore quantifies both the spatial characteristics and the depth of abdominal pigmentation.
This methodology quantifies the pigmentation of the third and fourth abdominal tergites, which have been the focus of numerous previous studies1,15,23,24,25,28,33,39,42, either exclusively or in combination with more posterior tergites. Although less variable than the fifth and sixth abdominal tergites, the third and fourth tergites are not completely pigmented in males, so this protocol can be applied to both males and females. Nevertheless, as shown here, the protocol can be used to measure pigmentation in the fifth and sixth abdominal tergites in females. Furthermore, minor modifications of the scripts used to extract the characteristics of the pigmentation profile should allow for the method to be used to quantify the variation in pigmentation in a wide variety of other organisms.

<table><tbody><tr><td>Dumont #5 Biology Forceps</td><td>FST</td><td>11252-30</td><td></td></tr><tr><td>Agar</td><td>Sigma-Aldrich</td><td>5040</td><td></td></tr><tr><td>Dissecting Scope</td><td>Leica</td><td>MZ16FA</td><td></td></tr><tr><td>Base</td><td>Leica</td><td>MDG41</td><td></td></tr><tr><td>Camera</td><td>Leica</td><td>DFC280</td><td></td></tr><tr><td>Gooseneck Cold Light Source</td><td>Schott</td><td>ACE 1</td><td></td></tr><tr><td>Image Acquisition Control Software</td><td>Micro-Manager v1.3.20</td><td></td><td>https://micro-manager.org/</td></tr><tr><td>Image Analysis Software</td><td>ImageJ</td><td></td><td>https://imagej.nih.gov/ij/</td></tr><tr><td>Data Analysis Software</td><td>R 3.3.2</td><td></td><td>https://www.r-project.org/</td></tr><tr><td>LED</td><td>Thor Labs</td><td>LEDWE-15</td><td></td></tr><tr><td>Multimeter</td><td>Fluke</td><td>Fluke 75 Series II</td><td></td></tr><tr><td>60 mm x 15 mm Petri dish</td><td>Celltreat Scientific Products</td><td>229663</td><td></td></tr><tr><td>Stage micrometer</td><td>Klarman Rulings, Inc.</td><td>KR-867</td><td></td></tr></tbody></table>

quantifying abdominal pigmentation in drosophila melanogaster

Quantifying Abdominal Pigmentation in Drosophila melanogaster

Pigmentation is a morphologically simple but highly variable trait that often has adaptive significance. It has served extensively as a model for understanding the development and evolution of morphological phenotypes. Abdominal pigmentation in Drosophila melanogaster has been particularly useful, allowing researchers to identify the loci that underlie inter- and intraspecific variations in morphology. Hitherto, however, D. melanogaster abdominal pigmentation has been largely assayed qualitatively, through scoring, rather than quantitatively, which limits the forms of statistical analysis that can be applied to pigmentation data. This work describes a new methodology that allows for the quantification of various aspects of the abdominal pigmentation pattern of adult D. melanogaster. The protocol includes specimen mounting, image capture, data extraction, and analysis. All the software used for image capture and analysis feature macros written for open-source image analysis. The advantage of this approach is the ability to precisely measure pigmentation traits using a methodology that is highly reproducible across different imaging systems. While the technique has been used to measure variation in the tergal pigmentation patterns of adult D. melanogaster, the methodology is flexible and broadly applicable to pigmentation patterns in myriad different organisms.

The protocol was used to explore the effect of rearing temperature on abdominal pigmentation. Previous studies have shown that an increase in developmental temperature results in a decrease in the spread of abdominal pigmentation in several species of Drosophila, including D. melanogaster30,32. Specifically, in abdominal tergites 3 and 4, the extent of pigmentation (width of the pigment band) decreases from 17 °C...

This work presents a method to quickly and precisely quantify the abdominal pigmentation of Drosophila melanogaster using digital image analysis. This method streamlines the procedures between phenotype acquisition and data analysis and includes specimen mounting, image acquisition, pixel value extraction, and trait measurement.

Pigmentation is a morphologically simple but highly variable trait that often has adaptive significance. It has served extensively as a model for ...

The overall goal of this methodology is to rapidly quantify abdominal pigmentation in the fruit fly Drosophila melanogaster. This method can help answer key questions in the field of evolutionary biology such as identifying the genetic loci that underlie in turn in trust-specific variation morphology and understanding the development and evolution of morphological phenotypes. The main advantage of this technique is that it allows users to non-destructively measure various aspects of abdominal pigmentation including the spread and depth of pigmentation.Though this method can provide insight into Drosophila melanogaster's abdominal pigmentation, it can also be applied to other Drosophila species and easily adapted to measure pigmentation patterns in other insects and animal taxa. Prior to imaging, the flies can be stored in 70%ethanol to maintain their pigmentation. Visualization requires a mounting pad.Load a 60 millimeter Petri dish with about 10 milliliters of 1.25%agar in water. Under a microscope, use fine forceps to dig a 20 millimeter long, two millimeter wide, one millimeter deep trench into the gel. Several trenches can be made in one dish.Then embed flies into the trench wi

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Learn to quantify abdominal pigmentation in Drosophila melanogaster using digital image analysis. This non-destructive method enables precise measurement of pigmentation spread and depth for evolutionary biology research.

Quantifying Abdominal Pigmentation in Drosophila melanogaster

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