DATA & PROTOCOLS » AFLP PROTOCOL

This protocol, currently (occasionally) used in the Wolf lab, has been adapted (by Paul Wolf and Mark Ellis) from several sources: The AFLP plant mapping guide from applied Biosystems, the AFLP protocols of Laboratoire de "Biologie des Populations d'altitude" (Grenoble. France), and the KeyGene protocols by Matt Gitzendanner (University of Florida). The original AFLP protocol was that of Vos et al. 1995 Nucleic Acids Research 23:4407-4414.

Running a Gel

Running an AFLP gel on the ABI is very similar to running an automated sequencing gel. The same 5% longRanger gel is used and all setup and loading is basically the same.

Loading dye:

For each tube (make master mix as usual):

  • 0.75 micoliters of deionized formamide

  • 0.15 microliters of blue loading dye (in GeneScan-500 box)

  • 0.3 microliters of GeneScan-500 ROX size standard

  • 1.5 micoliters selective reaction mix

Centrifuge briefly to get everything on the bottom of the tube.

Heat at 95 C for 2 min.

Cool rapidly on ice and keep on ice until and during loading.

Loading and running a gel:

When setting up the gel, use the GeneScan Run and GeneScan Sample for setting up the run and sample sheet. For the sample sheet, you need to fill in the information for each lane, and each dye color in each lane.

Load 1.5 micro liters of sample on the gel.

Run for 3 hrs.

Settings to note on run: Use the virtual filter set F:

Modules:

  • Plate check F

  • Prerun: GS PR 36F 2400

  • Run: GS run 36F 2400

Analyzing the Data

Step 1: Open GeneScan

  1. Open the gel tile you wish to analyze

  2. Select Gel> Adjust Gel Contrast (command-J)

    1. Move the top sliders down to increase the intensity of the color

    2. Move the bottom sliders up to reduce the threshold for the color

  3. Select Gel > Track Lanes...

    1. Click the Auto Track Lanes button

  4. When the tracker is done, check that the tracking lanes follow the lanes on the gel

    1. If the lanes are off drag the tracking lane to line them up with the lanes on the gel

  5. Note the scan numbers that correspond to the start and end of the data

    1. Select Settings > Analysis Parameters...

    2. In the upper left set the start and stop ranges that correspond to those scan lines

  6. Select Gel> Extract Lanes ... (command-L) and click OK

  7. The program goes through each lane and extracts the data, making an individual sample file for that lane. The sample files are all placed into a new folder within the folder that your gel file was in. Once all samples are extracted, the files are added to a project. Projects are used to collect samples for analysis, and can contain samples from multiple gels.

  8. Make a size standard for the samples from each gel:

    1. Select File > New... (command-N) and click on the Size standard icon

    2. Select a file to use for the size standard. You should pick one that worked well, and I generally choose one from near the middle of the gel. Click OK in the window that pops up next.

    3. A new window comes up with the red portion of the chromatogram for your sample. This is the size. standard peaks. Use the table and graph on pages A·6 and A-8 of the GeneScan Users Manual to identify the size of the peaks.

      1. Click on a peak to assign a size ..

      2. Leave extraneous peaks as size 0.

    4. Select File > Save ... (command-S) and save your size standard. Call it something to indicate which gel and which lane the standard was generated from

  9. Go back to the analysis window, and click and hold on the pull-down box next to the "Size. Standard" column header and select the file you just created. This will apply the size standard to all sample in the project

  10. Click on the four color boxes to select all colors for all samples. Then click the analyze. box.

  11. GeneScan will now go through each sample and do the size calling for all peaks based on the size standard you created earlier. When it is done a new window will open up ... the results control.

    1. Double check the accuracy of size calling by examining all of the red data. If some samples do not line up correctly, make a new size standard for those samples and re-analyze them.

  12. Save your project.

Step 2: Open Open Genotyper

  1. Select Edit > Set preferences ...

    1. Select one color to import and click OK

  2. Select File> Import > From GeneScan file (command~ !)

    1. Select the files you want to import either one-by-one or click the import all button

  3. Click on the Samples section of the Genotyper window. And Select Edit > Select All (command-A) to select all of your samples

  4. Select Analysis > Clear Category List

  5. Now we want to make a category that will determine which peaks will be scored. Only those peaks with a good signal in at least one individual will be scored. I usually set the good signal level at 300 fluorescent units.

    1. Select Category > Add Category... (command-L)

      1. Name your category something like: All peaks over 300

      2. I only look at peaks over 70bp so type 70 into the low Size box

      3. Click on the box next to the "with (scaled) height of at least'' option, and type 300 in the text box after that

      4. Click OK

    2. Select Analysis > Label peaks, and click OK to label the peaks with the size in base pairs. This will label all the peaks with a fluorescent intensity over 300 units.

    3. Select Category > Make from Labels ... (command-M)

      1. Unmark the "skip overlapping categories" box

      2. Type the prefix you want for the category names (color, primer set. .. )

      3. Select the dye color that is being analyzed

      4. Click OK

    4. Now you have a bunch a categories that correspond to the peaks that are over 300 fluorescent units in at least one individual. Now we need to score all of the individuals for those categories. To do that we need to label all of the peaks in all individuals (not just those over 300 units)

      1. Select Category > Add Category (command-L)

        1. Name your category something like: All peaks

        2. Unselect the peak height box

        3. Click OK

      2. Click in the categories box and select Edit > Unmark (command-U) to unmark all of the categories (notice that marked categories have a • in front of the category name). Then double click on, the All peaks category to remark it.

      3. Select Analysis > Label peaks to label all the peaks. Click OK

      4. Now remark all the categories. Select Edit > Mark (command-M)

      5. Unmark the two categories that you made by hand (All peaks and All peaks over 300)

    5. Now you are ready to make a table of the results

      1. Select Table > Add rows to table ...

      2. Click on the "More Choices" button

      3. In the "Contents per row" set of radio buttons, select "Sample"

      4. Click on the "Unmark All" button

      5. In the table setup box, double click on "Sample info" to select it (Now has a •)

      6. Then double click on the. "Labels" to select it

        1. The default setting for the labels is for each to take 2 columns in the table, but we only need one, so ... in the settings box on the right, change the "Number of columns:" to 1

      7. Click OK

    6. Select Table > Export to file ... and save the table

Step 3: Open Excel

  1. Select File > Open ... and select your table, which is a tab delimited text file. Excel will present you with a bunch of options for opening the table, simply hitting return and accepting the default for each will work fine.

  2. Modify your table in any way you want (shading every other row, bolding the header info, etc ... )

  3. Print this out

Step 4: Open GeneScan

  1. Open your project

  2. Select Window > Result ~ Control (command-2)

  3. Go through your samples (generally about 6 at a tim.) and for every category (now every column on your table) double check that you think that the sample was scored correctly

    1. If you think that there is a peak that was missed, make a note on you table.

    2. If you think that a region is too hard to interpret make a note.

    3. If you think two categories should be combined because they are really the same peak make a note.

    4. Basically make any adjustments to the data that you see fit.

Step 5: Go back to Excel and make changes.

Step 6: Now you have a table with the manually checked calls for each peak for each sample. Now you can manipulate that data around in order to get something that a population genetics/statistics program will handle. I have several rather clumsy scripts that might (or might not) be helpful. These were written when I was first learning to code, but they did work: https://github.com/Wolflab/AFLPs.

Step 7: You are DONE!!!