Technical Note: Genotyping

Analyzing FFPE Samples with Infinium® Microarrays
A streamlined workflow for analyzing FFPE samples in GenomeStudio® Data Analysis Software.

Introduction
Formalin-fixed, paraffin-embedded (FFPE) tissue samples provide aninvaluable resource and repository of information that can provide
insight into the underlying genetic mechanisms associated withdisease. These samples can be useful in biomarker discovery, drug
development, and cancer research, yielding high-quality data in wholegenome genotyping studies.
However, the fixation process and storage of FFPE samples
frequently leads to nucleic acid degradation and base modification.
Because it is inefficiently amplified in the whole-genome amplification
step, degraded DNA from FFPE samples generally results in poor
performance in array-based genotyping studies. Such samples
have traditionally been unusable with the Illumina Infinium assays. To
overcome this problem, the Infinium FFPE DNA Restore Kit provides
a simple workflow to repair damaged DNA, achieving high-quality
genotyping and copy number variation data in Infinium assays. Detailsof this workflow are described in the data sheet, Infinium FFPE DNA
Restoration Solution, Pub. No. 370-2010-009.
Furthermore, analyzing the data generated from FFPE samples
using standard cluster-fitting algorithms can be complicated. Often,
the performance differences between normal and FFPE samples
cause changes in the cluster positions of some markers, leading
to inaccurate genotyping and copy number calling. To increase theaccuracy of the genotyping software and to analyze data generated
from FFPE samples more effectively, special analysis procedures
are necessary to account for clustering differences. The most direct
method for managing the cluster-fitting algorithm is to identify thedifferentially performing markers (SNPs) and exclude them fromfurther analysis*.
This technical note describes a workflow (Figure 1) for repairingdamaged DNA and excluding differentially performing FFPE markers
from analysis with Illumina GenomeStudio Data Analysis Software.
Covering the entire range of Illumina human genotyping microarrays†(including iSelect® BeadChips) and assays, this method generates
high-quality clustering, genotyping, and CNV calling of Infinium Assaydata using algorithms in the Genotyping (GT) Module v2011.1/1.9.41.

* Experienced users may find it useful to examine differentially performing markers
in more detail and to recluster the markers in question. Information on cluster
fitting in GenomeStudio can be found in the technical note, Infinium Genotyping
Data Analysis2.
†Because the HumanCytoSNP-FFPE BeadChip has been enabled previously for use
with FFPE samples, the method described in this technical note does not apply. In
this case, the optimized protocol that accompanies the BeadChip is recommended.

Figure 1: FFPE Sample QC, Restoration, andExclusion Workflow
Purify DNA from FFPE samples

Assess quality with FFPE QC Kit

Restore degraded FFPE DNA with Infinium FFPE DNA Restore Kit

Perform Infinium Assay

Exclude differentially performing markers (SNPs)

Analyze clusters in GenomeStudio

Outlined is a streamlined workflow for analyzing FFPE samples. Included
are steps for sample quality control, sample restoration, and exclusion ofdifferentially performing markers for downstream use in GenomeStudio Data
Analysis Software. When processed in this manner, high-quality clustering,
genotyping, and CNV data can be generated from FFPE samples using anyof the Infinium Assays.

Simple FFPE Sample QC and Restoration
After DNA extraction using one of many commercially available kits,
the Illumina FFPE QC Kit is used to evaluate the quality of prospective
FFPE samples, determining if they are useable. The kit provides
primers for a real-time PCR assay that can be carried out on moststandard real-time PCR instruments.
Samples that pass the quality control evaluation are advanced throughthe DNA restoration process. Using a proprietary enzymatic reaction,
the Infinium FFPE DNA Restore Kit repairs degraded FFPE DNA
in preparation for the whole-genome amplification step in Infinium
Assays. Generally, over 80% of the FFPE samples that pass the QC
assay metric are successfully restored (Figure 2). For optimal assay
performance, minor modifications to some of the Infinium workflows
are required to increase the effectiveness of the whole-genome
amplification step. These modifications are summarized for each assay
in the following section.

Technical Note: Genotyping
Figure 2: QC of FFPE Samples

Excluding Differential Markers
Following the completion of the Infinium Assay, the generated raw data
are uploaded to GenomeStudio and evaluated as described in thefollowing sections.

Cluster Normal Samples
Cluster information for normal samples can be obtained directly from
Illumina-supplied cluster files as described in Option #1. When an
Illumina-supplied cluster file is unavailable (as with custom arrays),genotyping data from normal samples can be clustered as describedin Option #2.
• Option #1: Using the cluster file associated with the array used forgenotyping, create a project in GenomeStudio. Select the Index,Name, AA_R_Mean, AB_R_Mean, and BB_R_Mean columns for all
markers and export the data to a Microsoft Excel file named withthe suffix, “_Normal-intensities”.

DNA from 130 FFPE samples of varying quality and control DNA (2 ngeach) were analyzed in triplicate by real-time PCR. The average Cq value
for the control DNA was subtracted from Ct values for FFPE DNA. The
resulting Delta Ct values were plotted against the Infinium HD Assay
call rates for the same samples after restoration. Greater than 80% ofsamples with a QC value below 5 were successfully genotyped (orangebox). Depending on sample origin and age (1–35 years), 35–95% of
samples passed QC.

Infinium Assay Modifications
For both manual and automated workflows, the amplification stepshould be performed as instructed in the manual protocol with thefollowing modifications.
• Infinium HD Super Protocol: To prepare the MSA1 plate (“MakeMSA1 Plate” step), 8 μl of the repaired sample DNA, instead of thestandard 4 μl, are added to the corresponding wells in the MSA1 plate.
• Infinium HTS and HD Ultra Protocols: To prepare the MSA3plate (“Make MSA3 Plate” step), 8 μl of the repaired sample DNA,instead of the standard 4 μl, are added to the corresponding wellsin the MSA3 plate.
• Infinium LCG Protocol: To prepare the MSA6 plate (“MakeMSA6 Plate” step), 8 μl of the repaired sample DNA, instead of thestandard 4 μl, are added to the corresponding wells in the MSA6plate.
For all other Infinium assays, whole-genome amplification is performed as
instructed in the appropriate Infinium Assay Guides. Following amplification,
the remaining protocol steps are performed as recommended using either
the manual or automated workflows accordingly.

• Option #2: To cluster normal samples, all FFPE samples
are excluded and normal samples are processed using theGenomeStudio automated clustering algorithm. Preferably, at least
100 samples should be analyzed. If 100 samples are not available,
fewer samples can be used for clustering, yielding diminishingdata quality as the number of samples decreases. After clustering,
update the SNP statistics and output data from the SNP table. If
applicable, exclude samples that do not pass QC (outliers) using
call rate and p10 GC metrics, and recluster the remaining normalsamples. After clustering is complete, select the Index, Name,
AA_R_Mean, AB_R_Mean, and BB_R_Mean columns for allmarkers and export the data to an Excel file named with the suffix,“_Normal-intensities”.

Table 1: Excel Functions that Identify Differentially
Performing Loci
Differential
MetricFunction

AA_R_Meanabs[AA_R_Mean(Normal)-AA_R_Mean(FFPE)]

AB_R_Meanabs[AB_R_Mean(Normal)-AB_R_Mean(FFPE)]

BB_R_Meanabs[BB_R_Mean(Normal)-BB_R_Mean(FFPE)]

Results in the Function column of the Excel file correspond to the absolutevalue for the intensity differential between the AA_R_Mean, AB_R_Mean,and BB_R_Mean values of the normal and FFPE populations.

Technical Note: Genotyping
Cluster FFPE Samples
To cluster the FFPE samples, all normal samples are excluded andFFPE samples are processed using the GenomeStudio automatedclustering algorithm. Preferably, at least 100 samples should beanalyzed. If 100 samples are not available, fewer samples can beused for clustering, yielding diminishing data quality as the number ofsamples decreases. After clustering, update the SNP statistics andoutput data from the SNP table. If applicable, exclude samples that
do not pass QC (outliers) using call rate and p10 GC metrics, andrecluster the remaining FFPE samples. After clustering is complete,select the Index, Name, AA_R_Mean, AB_R_Mean, and BB_R_Meancolumns for all markers and export the data to an Excel file namedwith the suffix, “_FFPE-intensities”.

Compare Data Sets
After the normal and FFPE samples have been clustered inGenomeStudio and the data exported to Excel files, merge the data
sets into a single Excel file. Next, compare the absolute values of thedifferences between samples at each marker. Calculate theAA_R_Mean, AB_R_Mean, and BB_R_Mean differential metrics foreach marker and cluster type by the functions defined in Table 1.

Exclude Differentially Performing Markers
Rows in which any of the three differential metrics are greater than
0.25 are scored as 1. All other rows are scored as 0. The differential
0,1 column can now be imported into the GenomeStudio Genotyping
Module where markers defined as 1 are zeroed and excluded fromfurther analysis. Generally, approximately 10–30% of all markers areremoved in this manner.
After excluding differentially performing markers, standard cluster fittingin GenomeStudio can proceed to generate high-quality clustering,
genotyping, and CNV data as described in the technical note, Infinium
Genotyping Data Analysis2.

Summary
Archival FFPE samples hold an abundance of invaluable information
for many genomic studies, yet they often perform poorly in arraybased assays due to highly degraded DNA. The method forrepairing damaged DNA and excluding differentially performing
markers described in this technical note increases the accuracyof the GenomeStudio software and enables effective data analysis
from these samples. When processed in this manner, high-quality
clustering, genotyping, and CNV data can be generated from FFPE
samples using any of the Infinium Assays.

Learn More
For more information about GenomeStudio Software and supporting
documentation, visit www.illumina.com/informatics/sequencing-microarray-data-analysis/genomestudio.ilmn.
To learn more about the Infinium Genotyping Assays, visit
www.illumina.com/technology/infinium_hd_assay.ilmn.

References
1.

GenomeStudio Software package, Genotyping (GT) Module v2011.1/1.9.4(www.illumina.com/software/genomestudio_software.ilmn).

2.

Infinium Genotyping Data Analysis (www.illumina.com/documents/products/technotes/technote_infinium_genotyping_data_analysis.pdf).

Technical Note: Genotyping

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Pub. No. 970-2014-001 Current as of 23 April 2014