The MyGo Pro is capable of melting very slowly whilst continuously capturing fluorescence data. This allows the software to identify very small changes in PCR amplicons that can be used to classify specific genotypes. The MyGo Pro software can analyse this data and produce graphical representations of any small changes identified with the use of a difference curve.
To demonstrate HRM, we will use an example data file. Open the “MyGo Pro Class 1 SNP.ppf” file in the walkthrough data folder. Select the Profile tab. The example experiment shows an amplification followed by a HRM program. Note that the HRM program uses a low ramp rate of 0.05C/s, to allow for many optical acquisitions to be performed per celsius.
Click the Samples tab:
As for Melt Peaks analysis, the samples and targets for a HRM experiment are generally very simple. Assign samples as appropriate, and then create a single target using the appropriate HRM compatible dye, and assign that target as an unknown in each well containing a sample.
Select Analysis Type
Click the Analysis tab, then the Manual tab and add a High Resolution Melt analysis from the Select Analysis Type window. If not already present learn how to do this in the Selecting Analysis Type section.
Results as Table
Click the Results as Table tab, if it is not already selected. This shows the common features present in the Results as Table layout, as shown in General Table Layout. Additional columns include a Baseline and a Genotype column that will be covered in more detail further on in this section.
Samples as Plate
The Samples as Plate view shows the features described in Working with Plate Displays.
Click the Raw tab in the top left, if it is not already selected. This tab shows the basic controls for HRM analysis:
The Target: drop down control shows a list of all targets in the experiment. Select the target of interest to analyse it. Where multiple independent assays are performed in the same plate, you may want to use different targets for each assay, allowing you to choose which set of data to analyse. You can also create multiple analyses, one for each target.
Noise Reduction Range
This range will reduce noise when increased and improve resolution when decreased.
Click the Normalization tab towards the top left, and the Raw tab in the top right panel:
The Normalization Settings tab and Raw tab show a key aspect of the analysis of HRM data - normalisation of the raw melt curves.
The Raw pane shows a plot of the dye intensity versus temperature for each well. This data is not normalised or corrected in any way. The graph also shows two highlighted areas, labelled Initial and Final. These are the temperature ranges used to measure, within each curve, an initial dye intensity level and a final dye intensity level. These levels are then used to normalise each curve, placing it on the same intensity scale from 0 to 1, and more closely aligning the curves in the y axis of the graph. This normalisation removes the effect of background fluorescence, and variation in the brightness of different wells. The regions can both be moved, and should be placed before and after the region of temperatures where significant melting occurs.
The Normalization Settings tab also shows a table of Temperature Ranges, with each range (initial and final) defined by a pair of temperatures. These temperatures can be edited using the table as normal (double click the cell, or click it and type a number then enter).
Melt Curve Graph Tabs
All the graph tabs (*Raw*, Normalised, Shifted and Difference) support coloring of curves by either sample color or the color of the assigned genotype for the curve - genotypes will be described later, but for now use the Color by: drop down control to select the Sample option, so that curves are colored according to sample.
Editing Initial and Final Areas
The Raw data graph supports direct editing of the Initial and Final regions in the normal way - make sure that the region editing mode is selected, by clicking the “H” icon:
While using the region editing mode regions can be selected by clicking on either of the lines in the region. When a region is selected, it can be edited by moving the mouse over the line to be moved, then holding the left mouse button down while dragging the mouse.
Click the Normalised tab in the right hand side of the screen:
This changes the graph display to show normalised melt curves. The effect of normalisation can be seen, since the curves are now more closely aligned. In particular, the mean intensity of each of the curves is the same in both the initial and final regions.
Temperature Shifted Settings
Click the Temperature Shifted tab on the right and select Temp. Shift Settings on the left.
This enables all curves to be shifted in the temperature (x) axis to align the intersection of the curves and the intensity threshold. To see this effect, click the Temp. Shift Settings tab, and then click the Apply Temperature Shift selection box in the top right:
The temperature shift is not enabled, so the curves are not shifted in the x axis. This means that they do not (necessarily) all pass through the intensity threshold at the same temperature. Now click the Use Temperature Shift checkbox to select it:
Once enabled curves are shifted in the x axis and all pass through the intensity threshold at the same temperature. The curves are now more closely aligned, removing the effect of temperature non-uniformity or different melt temperatures, and making even small differences in shape more obvious. However some curves which could previously be distinguished by different melt temperatures are now placed on top of each other and cannot be distinguished.
The Temp. Shifted graph also shows the Intensity Threshold as a horizontal line. This is a graphical display of the same value edited by the Intensity Threshold number control in the Temp. Shift Settings pane. The Intensity Threshold value can be edited by clicking and moving the blue Intensity Threshold bar or entering a value in the Intensity Threshold entry box.
Bilinear Normalisation chooses between two methods of intensity normalisation:
When the checkbox is unselected (by default), the melt curve intensity is corrected according to a single linear function (essentially a scale and offset) in order to align melting curves in the y axis. The normalised curves are aligned by the mean dye intensity in the Initial and Final temperature regions.
When the checkbox is selected, the melt curve intensity is corrected according to a pair of linear functions. A first linear function is fitted to initial dye intensity, and used as the top end of the final corrected scale. A second linear function is fitted to final dye intensity, and used as the bottom end of the corrected scale. The corrected dye intensity data then varies from a normalised intensity of 0 at the level of the second linear function, to a normalised intensity of 1 at the level of the first linear function.
This correction will remove a large part of the temperature dependency of the dye, giving curves that may be easier to interpret.
The Normalised curves are now corrected further - the bilinear normalisation corrects the drift of dye intensity in both the Initial and Final regions, so that the curves are both aligned and horizontal in these regions. For some data this may make it easier to see the underlying melt features.
The Difference graph shows each curve as it appears when the baseline curve is subtracted from it, after normalisation (and temperature shift, if selected). This emphasises the differences in curve shape between the samples, allowing for example for HRM genotyping.
Selecting Baseline Curves
When no baseline wells are selected, the software will automatically select the first well so that at least one baseline well is selected at all times. The mean melting curve from the selected baseline wells with the addition of 2% of the remaining wells is used as a baseline curve: this baseline curve is subtracted from each individual melting curve, to prepare the Difference plot. Multiple baseline wells do not have to be chosen, however, selecting more baseline wells may improve difference plots. It does not matter which genotype you choose for a baseline, however it is important that only one genotype is chosen for baselining. In the example below all wells containing Heterozygote samples were selected as baseline wells:
Click the Difference tab:
Difference Graph With Temperature Shift Enabled
As explained previously, applying a temperature shift will make small differences in shape more obvious, however will make curves distinguished by different melt temperatures very similar. With this in mind the difference curve above is temperature shifted, making Wild-Type and Mutant curves very similar.
Difference Graph Without Temperature Shift Enabled
Below is the same difference graph, without temperature shift enabled. Notice that Wild-Type and Mutant curves are now very different as both shape and temperature are being used to differentiate them from one another.
In the example Experiment, the samples have been colored depending on their genotype prior to running the experiment. However, the user has the ability to assign samples with a genotype that has a specific color that can be sorted for in the graphs.
The Experiment contains three different genotypes. We will create labels for these genotypes. Click the “+” button in the Genotypes list pane, to create new genotypes. As many genotypes as required can be defined in the Genotypes list.
Editing Genotype Names and Colors
By default, the new genotypes are named “gen.”, with numbers added in brackets to ensure that the names are unique. The genotype names can be edited as normal, by double clicking the cells, or clicking the cells and typing a name then pressing enter. The genotypes also have a color and an optional note, which are edited in the usual way.
Assigning Genotypes to Samples
We will now assign genotypes to the samples. An easy way to do this is to use the Differences graph to select the curves for a particular genotype. This uses curve selection, described in more detail in the section on Working With Graphs.
Selecting Curves for Assigning Genotypes
Enable selection mode in the chart by selecting the second icon, showing a selection box. Then move the mouse so it is in the graph data area, above and to the left of the top of the black curves in the graph. Now hold down the left mouse button and drag the mouse so that a box is drawn around the black curves, being careful not to drag the box across any other curves. Now release the left mouse button.
The graph should now show the blue curves as selected, and other curves as unselected - if this is not the case, just repeat the previous step:
With the correct wells selected, we now need to select the appropriate genotype. For this example the blue curves (Mutant) will be assigned gen.2. Finally, press the Assign button between the Results as Table pane and the Genotypes pane:
This will assign the selected genotype to the selected wells - for example above we can now see that well A5 is one of the selected wells, and so is now marked as genotype “gen. 2”.
Clearing Assigned Genotypes
Genotypes can also be cleared by selecting the appropriate wells and clicking the Clear button.
Where curves cannot be clearly grouped you may wish to create a genotype called “Ambiguous” or similar, and use it to mark the ambiguous curves. You may even wish to exclude these wells from the HRM analysis, so that their curves are not visible on the graphs. This may make it easier to group the remaining curves.
Genotypes as Plate
Finally, click on the Genotypes as Plate to show the assignment of genotypes to each well:
The plate views can also be used when assigning genotypes to wells.