T-Cell Receptor Gamma
Capillary Electrophoresis Assays
Research Use Only (RUO)

www.invivoscribe.com
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inquiry@invivoscribe.com
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MM-0082 (RUO) Rev 04 February 2024

Table of Contents
1. Overview of Assays
2. Assay Performance Characteristics
3. Additional Positive Controls

5. Sample Interpretation

4. DNA Integrity

6. Protocol Tips: T-Cell Rceptor Gamma Gene
Rearrangement Assay 2.0
7. Quick Guide: IdentiClone RUO TCRG 2.0 Software
8. Available Products

1. Overview of Assays
Both Invivoscribe’s T-Cell Receptor Gamma Gene Rearrangement Assay 2.0 and TCRG Gene Clonality Assay were designed to
identify T-cell clonality in suspect lymphoproliferations and are to be used in conjunction with other laboratory tests and resultsinterpreted in the context of all available information. Despite this similarity, there are some noteworthy differences.
The TCRG Gene Clonality Assay includes two master mixes: TCRG Tube A and TCRG Tube B. TCRG Tube A contains primers thattarget the Vγ1-8 + Vγ10 genes and Jγ1.1, Jγ1.3, Jγ2.1, and Jγ2.3 genes (also known as JγP1, Jγ1, JγP2, and Jγ2, respectively), generating
4 polyclonal distribution size ranges. TCRG Tube B contains primers that target the Vγ9 + Vγ11 genes and Jγ1.1, Jγ1.3, Jγ2.1, and Jγ2.3
genes, generating 4 polyclonal distribution size ranges (see figure).
Conversely, the T-Cell Receptor Gamma Gene Rearrangement Assay 2.0 includes a single master mix, TCRG – 6FAM, whichtargets genes described in lymphoid malignancies, including the Vγ2, 3, 4, 5, 8, 9, 10, & 11 and Jγ1/Jγ2,JγP, and JγP1/JγP2 regions.
The resulting polyclonal background lies within a single valid size range, generating a more robust and easily interpreted signal incomparison to other TCRG clonality assays which have multiple valid size ranges. Moreover, this design is better suited to detect
TCRG gene rearrangements in FFPE samples, due to its smaller valid size range of 159 bp to 207 bp (see figure).
Some of the benefits of the T-Cell Receptor Gamma Gene Rearrangement 2.0 Assay include:• Allows a higher sample throughput with the single master mix assay• Offers easy setup and simpler interpretation than the two-tube approach• Generates smaller amplicon sizes, meaning better success when testing FFPE samples• Reduces the DNA required for testing by half by reducing PCR reactions from two to one

2Figure 1: GeneScan analysis indicating rearrangement valid size ranges generated from the same polyclonal sample with theassays listed below. Figure adapted from: Marine, A., et al., (2019) HemaSphere 3(3):e255.
(A) TCRG Gene Clonality Assay, TCRG Tube A master mix;(B) TCRG Gene Clonality Assay, TCRG Tube B master mix;(C) T-Cell Receptor Gamma Gene Rearrangement Assay 2.0, TCRG-6FAM master mix

2. Assay Performance Characteristics
These two assays were designed differently, thus the results generated with each assay are interpreted differently. The
primary improvements of the T-Cell Receptor Gamma Gene Rearrangement Assay 2.0 over the TCRG Gene Clonality Assay
are the addition of JγP target and consolidation of multiple polyclonal distributions into a single distribution. When PCR
products are grouped into a single distribution, it generates an increased signal, improving sensitivity and reducing the
likelihood of false positive from minor peaks in dispersed repertoires. For example, minor peaks in the Vγ11 valid size range
can be mistakenly reported as significant due to lack of other polyclonal peaks within that distribution.
Because the T-Cell Receptor Gamma Gene Rearrangement Assay 2.0 targets more regions compared to the TCRG Gene
Clonality Assay, it detects more types of rearrangements. Furthermore, the different primer designs used by these assays
could exhibit variability when comparing results generated by the two assays. If a primer binding site utilized by the T-Cell
Receptor Gamma Gene Rearrangement Assay 2.0 is mutated, the intended primer may not bind efficiently and result in low
amplification of the target in question; TCRG Gene Clonality Assay primers may bind at a different location and amplify thesame target. The opposite may be true as well.
Overall, we do expect a high degree of concordance between the two assays, but it is not expected to be 100%, as these aredifferent assays with unique primer designs. The following references compare the and describe the characteristics andworkflow parameters of the one-tube and/or two-tube assays:
1. Assay Design Affects the Interpretation of T-Cell Receptor Gamma Gene Rearrangements1
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2963914/
2. A Single-Tube, EuroClonality-Inspired, TRG Clonality Multiplex PCR Aids Management of Patients with Enteropathic Diseases,
including from Formaldehyde-Fixed, Paraffin-Embedded Tissues2
https://jmd.amjpathol.org/article/S1525-1578(18)30173-9/pdf
3. A New and Simple TRG Multiplex PCR Assay for Assessment of T-cell Clonality3
https://journals.lww.com/hemasphere/Fulltext/2019/06000/A_New_and_Simple_TRG_Multiplex_PCR_Assay_for.8.aspx

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3. Additional Positive Controls
While both assay kits include positive and negative controls, Invivoscribe offers additional controls that are compatible with thesekits. Please see Table 1 for details.
Table 1. Positive Controls Compatible with either or both TCRG assays
Product Size(s)Part Number

Description
TCRG Gene Clonality Assay

T-Cell Receptor Gamma Gene
Rearrangement Assay 2.040880190

100% IVS-0004 Clonal Control DNA

TCRG Tube A: 211 bp
TCRG Tube B: n/a

TCRG – 6FAM: 179 bp and 188 bp

40880430

100% IVS-0008 Clonal Control DNA

TCRG Tube A: 218 bp and 229 bp
TCRG Tube B: n/a

TCRG – 6FAM: 195 bp and 207 bp

40880490

100% IVS-0009 Clonal Control DNA

TCRG Tube A: 212 bp
TCRG Tube B: 115 bp

TCRG – 6FAM: 188 bp and 191 bp

40881210

100% IVS-0021 Clonal Control DNA

TCRG Tube A: 211 bp
TCRG Tube B: 143 bp and 167 bp

TCRG – 6FAM: 183 bp and 188 bp

4. Sample Integrity
Invivoscribe capillary fluorescence assays generate robust results using genomic DNA (gDNA) extracted from a wide array of
specimen types. If the integrity of the sample is in question, the Specimen Control Size Ladder master mix can be used to verify
the quality and quantity of the extracted gDNA is suitable to generate results with Invivoscribe assays. Specimen Control Size
Ladder master mixes are included with most Invivoscribe kits, including the T-Cell Receptor Gamma Gene Rearrangement
Assay 2.0. Examples of the expected results for Gel and ABI Fluorescence detection with this master mix are shown in Figure 2,
respectively:
Figure 2: Expected results amplifying gDNA with: (Right) the Specimen Control Size Ladder - Unlabeled for Gel Detection (Catalog#20960020). Expected product size are indicated in red; a 100 bp ladder is also shown for size reference. (Below) the Specimen Control Size
Ladder – 6FAM for ABI Fluorescence Detection (Catalog #20960021). Expected product sizes are indicated in red and actual product sizes areindicated in black.

45. Sample Interpretation
Many publications have indicated T-cell receptor gamma gene rearrangement analysis is useful as an ancillary test in the diagnosis
of T-cell neoplasms.1-6 However, the design of the assay can have a large impact on assay interpretation, correlating increasing
assay complexity with more complicated and difficult interpretation.1,3
The T-Cell Receptor Gamma Gene Rearrangement Assay 2.0 was designed with this consideration in mind, simplifying
interpretation by using an individual, yet comprehensive, master mix labeled with one fluorochrome that generates a single,
robust valid size range. This is a major improvement in comparison to the TCRG Gene Clonality Assay, which uses two mastermixes labeled with two fluorochromes that generate a total of eight valid size ranges for interpretation. A comparison of assay
interpretation guidelines is provided in Table 2.
The higher complexity of the TCRG Gene Clonality Assay can lead to false positive results due to low-amplitude polyclonal
distributions with pseudoclonal peaks.1 Because of the limited repertoire generated by TRG rearrangements, amplificationof a sample with a high tumor load and limited number of T-cells can generate products that appear to be (oligo)clonal or
pseudoclonal.6
Table 2. Comparison of Invivoscribe TCRG Assay Interpretation Guidelines
Interpretation by Assay
TCRG Gene Clonality Assay
Valid Size Range
TCRG Tube A: 145 bp – 255 bp
TCRG Tube B: 80 bp – 220 bp*
1 or 2 significant peaks within the valid size range(s).
Significant Peak: 3X amplitude of 3rd highest peakwithin the same polyclonal distribution

N/A
Absence of significant peaks within thevalid size range(s)T-Cell Receptor Gamma Gene
Rearrangement Assay 2.0

Final Call (Sample Report)

Valid Size Range
TCRG – 6FAM: 159 bp – 207 bp
1 or 2 significant peaks within the valid size range
Significant Peak: 3X amplitude of lower neighboring peak
3 or more significant peaks within the valid size range
Significant Peak: 3X amplitude of lower neighboring peak
Absence of significant peaks within the valid size range

Detection of TCRG Gene
Rearrangements, consistent
with the presence of a clonal cell
population.
Detection of TCRG Gene
Rearrangements, consistent withthe detection of biclonality or
oligoclonality.
Negative for detection of TCRG
Gene Rearrangements.

*Interpret peaks within context of all sample information.

Sample Analysis and Interpretation using the IdentiClone® RUO TCRG 2.0 software
The IdentiClone RUO TCRG 2.0 software provides an objective interpretation of raw data files (FSA) generated by ABI 3500 and
ABI 3500xL instruments to identify clonal gene rearrangements in unknown samples. Software interpretation includes assessmentof the raw data files (FSA) generated by the ABI 3500/3500xL instruments while referencing a configured platemap for sample
traceability. Each master mix test set, including samples, a positive control, a negative control, and a no template control, isconsidered as a “run.” These runs can be configured individually using the Software Plate Setup function and loaded onto the sameplate along with additional runs. After detection is complete, the data files are uploaded to the Software, which proceeds withanalysis, referencing the platemap to complete the analysis for that sample.

56. Protocol Tips: T-Cell Receptor Gamma Gene Rearrangement Assay 2.0
Importing Plate Layout into GeneMapper
1. Open a new project and select Microsatellite for the project type.
2. Add raw data files derived from CE analysis to the project using the Add samples to Project icon in the toolbar.
3. Once the samples are added, verify that Analysis Method selected is Microsatellite Default and that the appropriate Size Standard isselected.
• If necessary, select samples and press the Analyze green play button in the toolbar.
• There will be a green, yellow, or red symbol in the SQ column for each analyzed sample.
4. If the symbol is red, the software will not calculate the peak sizes or display the sample data. In this case, view the size standard
chart by selecting samples and clicking the Size Match Editor icon in the toolbar to verify the peak sizes were correctly identified.
• If the SQ peaks were called correctly, click Override SQ, and then Apply.
• If some peaks were called incorrectly, re-assign the peaks by right clicking and selecting the correct size values.
		
		
		
		

o The GS 400 HD ROX size standard provides 21 labeled fragments of: 50, 60, 90, 100, 120, 150, 160, 180, 190, 200, 220, 240, 260, 280, 290,
300, 320, 340, 360, 380, and 400 nucleotides (nt).
o The GS 600 LIZ Size Standard provides 36 single-stranded labeled fragments of: 20, 40, 60, 80, 100, 114, 120, 140, 160, 180, 200, 214, 220,
240, 250, 260, 280, 300, 314, 320, 340, 360, 380, 400, 414, 420, 440, 460, 480, 500, 514, 520, 540, 560, 580 and 600 nt.

5. Select any samples that have a green play button in the Status column of the GeneMapper table and press the Analyze green
play button in the toolbar.
• Please note, it may be necessary to lower the Minimum Peak Height threshold in order to detect all peaks in a Gaussian 		
distribution:
		
		
		

o Select GeneMapper Manager from the Tools menu, navigate to the Analysis Methods tab, and open the Microsatellite Default 		
Analysis Method Editor.
o Navigate to the Peak Detector tab, select User Specified (rfu) toggle, and input the desired peak height for 6FAM dye.

• If changes are made, click the Analyze green play button in the toolbar.
6. In the GeneMapper table, highlight the samples of interest and select Display Plots in the GeneMapper toolbar.
7. Once the Display Plot is open, verify that Microsatellite Default is selected in Plot Settings and the appropriate fluorophoreis selected (6FAM).
• Select/Deselect the associated colored boxes in the toolbar, OR navigate to the View menu in the Display Plot, select Dyes,
and select the appropriate dyes.
		o As a reminder, 6FAM is Blue, HEX is Green, NED is Yellow or Black and ROX is Red in GeneMapper v4.0.

8. In order to view the peak size and height, select the Sizing Table icon in the toolbar.

Recommended Injection Parameters and Peak Detector Settings for the T-Cell Receptor Gamma
Gene Rearrangement Assay 2.0
Injection Parameters*
Parameter

Injection
Time

Injection
Voltage

Capillary
LengthPolymer

Dye SetOven
Temp

Run Time

Run
Voltage

PreRunTime

PreRunVoltage

Data
Delay

Value

7 sec.

1.0 kVolts

50 cm

POP7

G5

60°C

1630 sec.

19.5 kVolts

180 sec.

15 kVolts

1 sec.

Peak
Detector
Algorithm

Minimum
Peak
HeightBlue

OrangeValid Size
Range

Basic

User
Specified
(RFU)

50

50

159 bp 207 bp

Peak Detector Settings*
Parameter

Value*Please refer to the user manual for further instructions.

6Analyzing Samples in GeneMapper• Examine all assay controls prior to interpretation of sample results. If the controls do not yield the correct results, the assay is not
valid and the samples should not be interpreted.
• When analyzing the samples in GeneMapper, only analyze peaks within the valid size range of the master mix.
• To determine whether a peak is clonal or polyclonal, compare the height of the peak to the height of the polyclonal backgroundwithin the same sample.
o A validation study is recommended to determine an appropriate peak height ratio.

• Do not use RFU values to determine whether a peak is clonal, as RFU values can be affected by a variety of factors, such as thecapillary array and laser life.

Troubleshooting Size Quality (SQ) Error(s)A SQ Error indicates that GeneMapper did not identify the size standard peaks correctly, causing the generated products
to be identified at an incorrect size. Most SQ errors are caused by saturated signal(s), resulting in spectral pullup andmis-identification of peak sizes. If this type of error is observed in undiluted positive controls and the size standard peaks are identified
correctly or corrected, the SQ Error is of no significance since control validity relies on the presence or absenceof a peak at the expected size. However, if signal saturation is observed in the negative control, sensitivity controls, or unknown
samples, the run must be repeated on the ABI instrument to prevent result misinterpretation. Before repeating the ABI run with samples
exhibiting saturated signal(s), adjust the injection conditions and/or dilute amplified products. Please note that diluting unknown
sample amplicons could dilute a weak clonal product below the assay level of detection. The steps below will correct SQ Errors:
1. Verify the size standard peaks are correctly identified in the GeneMapper software prior to reviewing the data by selecting thesamples then clicking the Size Match Editor icon in the tool bar.
2. If the peaks labeled with SQ Errors were called correctly, click Override SQ, then click Apply.
3. If the size standard peaks are identified incorrectly, (in the Size Match Editor) manually reassign the ROX size standard peaks
to match the expected sizes: Right click on the incorrect size value and select the correct size value, then click the Override SQ button.
4. Repeat step(s) 2 or 3, above, for all samples indicating an SQ Error based on the peak size verification result (step 1).
5. Click the Analyze green play button to reanalyze the data.
• The data will update to display the revised product sizes.
If SQ Errors continue to occur, recalibrate the ABI instrument per the manufacturer instructions. Further optimization to reduce thenumber of SQ Errors includes adjusting the volume of size standard added to each well of the ABI plate.

Troubleshooting Miscalled/Unidentified Peaks
Another potential issue that may be encountered includes unidentified peaks which are miscalled as belonging to an adjacentpeak. This phenomena occurs when the electropherogram indicates two adjacent peaks and the peak table only indicates
one peak. Subsequently, when this data is pasted into the Algorithm Worksheet, the calculation does not identify a potentiallysignificant peak because there is no adjacent peak to which it can be compared. This can easily be remedied by changing thePeak Detection settings in GeneMapper, as the software uses the settings Polynomial Degree and Peak Window Size to determine
the start and end of each peak. The default value for Polynomial Degree is 3 and Peak Window Size is 15. Please see Thermo
Fisher language regarding these settings below:7• Polynomial Degree and Peak Window Size settings affect the peak detection sensitivity. Adjust these parameters to detecta single base pair difference while minimizing the detection of shoulder effects and/or noise (see Table 3 and Figure 3).
Table 3. Change peak detection sensitivity using Polynomial Degree and Peak Window Size
Function

Polynomial Degree Value

Peak Window SizeValue

Increase Sensitivity

HigherLower

Decrease Sensitivity

Lower

Higher7

• The peak window size functions with the polynomial degree to set the sensitivity of peak detection. The peak detector calculates the first
derivative of a polynomial curve fitted to the data within a window that is centered on each data point in the analysis range.
• Using curves with larger polynomial degree values allows the curve to more closely approximate the signal and, therefore, the peak detector
captures more of the peak structure in the electropherogram.
• The peak window size sets the width (in data points) of the window to which the polynomial curve is fitted to data:				o Higher peak window size values smooth out the polynomial curve, which limits the structure being detected.
o Smaller window size values capture more of the peak structure.

To adjust these settings, follow the steps below:
1. Open GeneMapper and from the top menu, select Tools, then GeneMapper Manager.
2. Navigate to the Analysis Methods tab to view available analysis methods.
• An existing Analysis Method can be edited, or (the preferred option) an existing Analysis Method can be edited then saved with a new name.

3. Select Save as… to create a copy of the selected analysis method with a new name.
4. Select the Analysis Method created in the previous step and click Open.
5. Navigate to the Peak Detector tab, and set Peak Detection Algorithm to Advanced.
• The Peak Window Size and Polynomial Degree settings can now be altered.

6. Test a few different conditions with a sample set to identify the optimal settings for this instrument.
• Use the guidelines in Table 3 to determine how to adjust these settings based on the observed issue and anticipated resolution.

Figure 3. Sample data generated with GeneMapper using the default Peak Detection Algorithm settings vs. optimized Peak
Detection Algorithm settings.
Default Peak Detection Algorithm settings: Polynomial Degree = 3; Peak Window Size = 15. Notice the peak indicated by the red arrow is not
identified in the peak table, rendering the 173 bp peak as not significant (since it is compared to the higher peak on the left).

8Optimized Peak Detection Algorithm settings: Polynomial Degree = 3; Peak Window Size = 11. Notice the peak indicated by the red arrow is now
identified in the peak table, rendering the 173 bp peak as significant (since it is now compared to the lower peak on the right).

7. IdentiClone RUO TCRG 2.0 Software Operational Instructions
Plate Setup Function
1. Open the IdentiClone RUO TCRG 2.0 Software.
2. Create a plate map using the Plate Setup function.
3. Enter information into the 4 fields located above the plate map: Plate Name, Results Group, File Name Convention, andBarcode (Optional)• These fields are limited to 50 characters or less and may only include letters (A-Z, a-z), numbers (0-9), hyphen (-) and underscore (_).
No spaces or special characters (other than specified) will be accepted.
• File Name Convention and Results Group will be automatically populated with default settings.

4. Configure runs to be included on the plate map.

• Runs must be configured before annotating the plate.
• Up to 24 runs can be configured per plate (A run represents a set of controls and corresponding samples).

5. Select each well assigned to a run and enter required information on the right side of the window. Save well following
verification of information.
• Select the appropriate Sample Type from the designated dropdown box: PC, NC, NTC or Sample.
• Enter Sample Name, a unique identification associated with a patient sample.
• Confirm that the correct Run is assigned to the sample.
• (Optional) Enter Notes, if any.

Platemap rules:• Each run must include a Positive, Negative and No Template Control; these controls will be indicated on the platemap as PC(positive control), NC (negative control), and NTC (no template control)• Fields marked with asterisk (*) are required to save a well.
• The fields Sample Name and Notes may only contain 50 characters or less.
• Sample Name can only include letters (A-Z, a-z), numbers (0-9), hyphens (-) and underscores (_). No spaces or special characters(other than specified) are allowed.
• The highlighted well position in the Plate Setup will become bold once all parameters are defined and saved for a particular sample
or control.

6. Upon defining and saving all samples and controls for every run in the plate, click Save Plate.
7. Select the directory filepath for the output files (CSV and LIVS).

• The CSV file contains platemap information and will be imported to the ABI 3500xL or ABI 3500xL Dx Genetic Analyzer.
• The LIVS file contains platemap specific data required for analysis and will be used in conjunction with the resective ABI 3500xL or ABI 		
3500xL Dx result files (i.e., FSA file).

Important: Once generated, do NOT alter CSV and LIVS. If any further modifications are needed, generate a new platemap to obtain a new setof paired CSV and LIVS output files.

8. Save/Print PDF template of plate map (Optional).

9Analysis Function
1. Open the IdentiClone RUO TCRG 2.0 Software.
2. Select the Analysis tool from the home user Interface.

• Verify that both FSA and LIVS files for the associated run(s) and plate(s) are located in the same directory filepath.

3. Click Analyze FSA and LIVS files (Figure 18).

• Navigate to the directory filepath containing the FSA and LIVS files, select the folder, and confirm the selection. Multiple plates canbe processed simultaneously, provided all corresponding LIVS and FSA files are present within the selected folder, including thosein nested folders.

Important: Do not edit FSA files generated by the ABI 3500xL platform. These FSA files are validated with LIVS files from the software. Uploading
files incorrectly will halt analysis process. An error message window will pop-up with a corresponding error code. (See Table 3) Sample results are
generated at this time. These results are for Research Use Only purposes and should not be used for any determination of medical diagnosis.

4. Select samples for report generation ( )• Click checkbox ( ) to toggle the selection of any run report or sample report• If a run is invalid, no sample reports will be selectable for samples from that run.

5. Click Generate Reports. Select directory for reports to be saved, Click Select Folder.
• A report password is set by the Admin user and is required to view the PDF reports.
• Results are grouped by Sample Name

6. A Run Report is generated by the software for every run selected following analysis.

• Traceable run information and control validity is recorded on Page 1 of the Run Report generated by the software• A summary of samples included in a run is included starting on Page 2 of the Run Report generated by the software

7. A Sample Report is generated by the software for every sample selected following analysis.

• Sample information and sample result are recorded in the Sample Report generated by the software.
• Run information is included in the Sample Report to provide traceability

8. Available Products
Catalog Number

Description

Quantity

12070101

T-Cell Receptor Gamma Gene Rearrangement Assay 2.0

33 reactions

12070111

T-cell Receptor Gamma Gene Rearrangement Assay 2.0 MegaKit

330 reactions

S1000001

IdentiClone® RUO TCRG 2.0 Software

1 software package

These products are for Research Use Only. Not for use in diagnostic procedures.

References 1. Cushman-Vokoun, AM et al., (2010) Journal of Molecular Diagnostics 12(6):787-796. doi: 10.2353/jmoldx.2010.090183 | 2. Derrieux, C et al., (2019) Journal of Molecular Diagnostics
21(1): 111-122. doi: https://doi.org/10.1016/j.jmoldx.2018.08.006 | 3. Armand, M et al., (2019) Hemasphere 3(3): e255. doi: 10.1097/HS9.0000000000000255 | 4. Langerak, A et al., (2012) Leukemia
26, 2159–2171. doi: https://doi.org/10.1038/leu.2012.246. | 5. van Krieken, J et al., (2007) Leukemia 21, 201–206. doi: https://doi.org/10.1038/sj.leu.2404467 | 6. van Dongen, J et al., (2003) Leukemia
17, 2257–2317. doi: https://doi.org/10.1038/sj.leu.2403202 | 7. Applied Biosystems 3500/3500xL Genetic Analyzer User Guide (Part Number 4401661 Version: c). https://tools.thermofisher.com/
content/sfs/manuals/4401661.pdf

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