Affymetrix® Mismatch (MM) Probes: Useful After All

Robert M. Flight¹, Abdallah M Eteleeb² and Eric C Rouchka²

¹ Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, Kentucky, USA 40292

² Department of Computer Engineering and Computer Science, University of Louisville, Louisville, Kentucky, USA 40292

Email Contacts

robert dot flight near louisville dot edu

ametel01 near louisville dot edu

eric dot rouchka near louisville dot edu

ABSTRACT

Affymetrix® GeneChip® microarray design define probe sets consisting of 11, 16, or 20 distinct 25 base pair (BP) probes for determining mRNA expression for a specific gene, which may be covered by one or more probe sets. Each probe has a corresponding perfect match (PM) and mismatch (MM) set. Traditional analytical techniques have either used the MM probes to determine the level of cross-hybridization or reliability of the PM probe, or have been completely ignored. Given the availability of reference genome sequences, we have reanalyzed the mapping of both PM and MM probes to reference genomes in transcript regions. Our results suggest that depending of the species of interest, 66%-93% of the PM probes can be used reliably in terms of single unique matches to the genome, while a small number of the MM probes (typically less than 1%) could be incorporated into the analysis. In addition, we have examined the mapping of PM and MM probes to five different human genome projects, resulting in approximately a 70% overlap of uniquely mapping PM probes, and a subset of 161 uniquely mapping MM probes commonly found in all five projects, 24 of which are found within annotated exonic regions. These results suggest that individual variation in transcriptome regions provides an additional complexity to microarray data analysis. Given these results, we conclude that the development of custom chip definition files (CDFs) should include MM probe sequences to provide the most effective means of transcriptome analysis of Affymetrix® GeneChip® arrays.

Categories and Subject Descriptors: J.3 [Life and Medical Sciences]: Biology and Genetics

General Terms: Algorithms, Measurement, Theory

Keywords: Bioinformatics, microarray, probe set, custom definition files.

INTRODUCTION

Oligonucleotide-based microarray technologies provide a methodology whereby a researcher can indirectly measure the expression level of an mRNA molecule being actively transcribed under a set of conditions by labeling a cDNA fragment that hybridizes to a complementary probe sequence specific to a particular transcript. Since their first use on customized cDNA arrays [1] in the mid-1990s, they have been used as the de-facto standard for measuring global transcriptional changes under differing conditions. While RNA-Seq [2] may eventually supplant microarrays as the method of choice, a large number of microarray experiments exist that have been deposited into publicly available repositories such as NCBI’s Gene Expression Omnibus (GEO) [3] and EBI’s ArrayExpress [4]. As a case in point, GEO contains 32,471 series as of 9/6/2012. The majority of the entries in GEO were performed on arrays designed by companies such as Affymetrix®, Inc. (Santa Clara, CA), Agilent Technologies, Inc. (Santa Clara, CA), Illumina®, Inc. (San Diego, CA), and GE Healthcare Lifesciences (Piscataway, NJ), with nearly half of the series (16,181) being performed on various Affymetrix® arrays.

The design of Affymetrix® GeneChip® arrays in particular provides for probe sets consisting of 11, 16, or 20 distinct 25 base pair (BP) probes, with each probe having a corresponding perfect match (PM) and mismatch (MM) probe. The PM and MM differ by the exchange of the complementary base at the 13th position in the probe. While MM probes were originally designed to account for signal in the PM resulting from non-specific cross-hybridization, they are often underutilized or completely ignored. Mismatch probes have been explored for use in long oligonucleotide arrays as well [5], but their utilization is limited to the Affymetrix® platform.

Affymetrix® provides a default GeneChip® analysis package known as the Micro Array Suite 5.0 (MAS 5.0) [6] that measures the signal intensity for a particular probe pair as:

\[ \begin{aligned} \text{signal} = TukeyBiweight ( \log (PM_{j} - MM^{*}_{j}) ) \end{aligned} \]

Where MM* is a modified version of MM that is never bigger than the intensity value of the PM. The motivation behind the modified mismatch intensity MM* is to report all probe-level intensities as positive values, and to remove the influence of the minority of probes where the MM intensity value is significantly higher than the corresponding PM intensity. In addition to the intensity signal, MAS 5.0 also produces a detection p-value which flags a transcript as “P” (present), “M” (marginal), or “A” (absent) based on the reliability of the probe set based on differences between PM and MM intensities.

Known issues in the use of PM and MM probe intensities to generate a single probe set intensity values led to the development of other approaches, including RMA [7] and GCRMA [8] which completely ignore the MM probes.

With the availability of individual probe and reference genome sequences, it is possible to re-map probes based on new sources of genome annotations. This allows custom Chip Description Files (CDFs) wherein probes are grouped into novel probe sets based on exon, transcript, and gene level annotation [9-22]. Most notable is the effort of the BrainArray group [10] which updates custom CDFs for a large number of Affymetrix® GeneChips® by creating probe sets based on annotated features such as Entrez Gene [23], Ensembl transcript, Ensembl gene, and RefSeq Gene [24]. Using custom CDFs has been shown to impact the reliability of expression analysis [10, 20-22, 25]. However, to the authors’ knowledge, only the PM probe sequences are used when generating custom CDFs.

Based on the observation that a small, yet significant number of PM-MM probe pairs exist where the MM intensity is significantly increased over the PM intensity, our initial inclination was that these differences in intensities were not due to cross-hybridization or rogue probes alone. Therefore, keeping in mind that Affymetrix® probes have been designed according to continually evolving genome assemblies, we proceeded to analyze PM and MM probes across eight commonly studied species (Table 1) by looking at PM and MM probes that uniquely map to the respective genome.

In addition to changing functional annotations, one potential problem area for microarray probe design is the presence of single nucleotide polymorphisms (SNPs) within a population. As the probes are designed using a reference genome or transcriptome, a “one-size fits all” approach has been taken for the probes on a particular array. However, SNPs are known to occur relatively frequently throughout the genome, with build 137 of dbSNP [26] containing over 53.5 million reference SNPs for the human genome. We have previously studied the effects of SNPs on Affymetrix® GeneChips® [27] showing that a large number of SNPs lie in the areas where microarray probes have been designed. This has been taken into account in the BrainArray’s custom CDF files which incorporate SNP information. To study the effects that individual variation can play in microarray analysis, we looked at the mappings of PM and MM probes within five distinct publicly available assemblies of human genomes.

METHODS

Mapping of PM and MM Probes

Chromosomal-based genome assemblies were downloaded from the UCSC Goldenpath Genomes ftp server using an anonymous login (ftp://hgdownload.cse.ucsc.edu/goldenPath/) [28] for eight commonly studied species, including C. elegans (roundworm), D. melanogaster (fruit fly), S. cerevisiae (baker’s yeast), X. tropicalis (western clawed frog), D. rerio (zebrafish), M. musculus (house mouse), R. norvegicus (brown Norway rat), and H. sapiens (human) (Table 1). Genome indices were created using bowtie-build version 0.12.8 [29] with the default parameters. Perfect match (PM) probe sequences for Affymetrix® GeneChips® were obtained from Bioconductor (v 2.10) probe packages, which are constructed from data available in NetAffx (Table 2) with each new Bioconductor release. Mismatch (MM) probe sequences were constructed by replacing the 13th base in the supplied PM probe sequence with the complementary base. PM and MM probes were aligned to the indexed genomes using bowtie version 0.12.8 [29] with the parameters –v 0 and –a which used together will report all valid probes matching with 100% identity.

Table 1. Genome assemblies used

Table 2. Affymetrix® GeneChips® used

Generation of Exons and Overlap

Exon regions were obtained from the UCSC genome browser as BED files with an entry for each exon. mergeBed from the bedTools suite was used to merge overlapping exons from multiple transcripts into single contiguous exons. These merged exons were used when defining overlaps of probe alignments with an exon. Probe and exon overlaps were defined as any type of overlap with at least 23 bases overlapping on the same strand. Overlaps were determined using Genomic Ranges version 1.8.7 [31].

DNA Microarray Data

For each GeneChip®, CEL files were downloaded from GEO for 20 random samples (with the exception of S. cerevisiae (12) and X. tropicalis (4), the GSMs are listed in gsmFiles.txt). Probe intensities were background corrected using the MAS background correction method implemented in Bioconductor. Depending on the application, intensities were log (base 2), square root transformed, or used as is.

Negative PM-MM Set

A PM-MM set of probes was considered to be negative if nine (two for S. cerevisiae and six for X. tropicalis) or more samples had a negative value for the difference in the PM-MM intensities. For examination of intensity distribution, any PM-MM pair with a negative different greater than 1000 in one or more samples was considered and examined.

Probe Correlations

For each MM probe that uniquely overlapped one merged exon (designated as a true-match MM, (TM^mm)), the correlation with all other MM probes in the probe set (mm) and the correlation with all other TM probes that also mapped uniquely to the same exon (if there were three or more other probes also mapped to the exon) was calculated ™.

Human Variation

To gain an understanding of individual variation and the unique mapping of microarray probes, five whole genome assemblies were downloaded for the human genome 32-36). Probes from the HGU133APlus2.0 Affymetrix® GeneChip® were aligned to each of these genomes using the methods previously described for mapping PM and MM probes.

Table 3. Whole human genome sequencing projects

¹Celera assembly consists of one African-American, one Asian-Chinese, one Hispanic-Mexican, and two Caucasians.

RESULTS

Probes Matching Genomic Locations

Given the PM probe sequences and the inferred MM sequences, individual probes were mapped to the corresponding genome assembly as outlined in Methods. The percentage of perfect match probes mapping to the genome ranged from a low of 80% (X. tropicalis) to a high of 95% (D. melanogaster), with the exception of S. cerevisiae (Table 4). It must be noted that the lower percentage of S. cerevisiae matches (53%) is expected, as the Yeast Genome 2.0 GeneChip® contains probes for two yeast species, S. cerevisiae and S. pombe.

Table 4. GeneChip® probes mapping to reference genomes

Affymetrix® probesets are given suffix definitions depending upon the uniqueness of the exemplar sequence used to design a probe set. A designation of _at indicates the probe set perfectly matches a single transcript; _a_at probe sets only perfectly match transcripts of the same gene; _s_at perfectly match multiple transcripts for the same gene family; and _x_at indicates the probe set is identical or highly similar to other genes. One of the difficulties with these designations is that it relies upon a set of annotations at a particular point in time.

Analysis of the probes that map to the genome (Table 4) indicates that 82% to 98% of the mapped probes map uniquely to a single genomic location. The fact that a number of probes map to multiple locations is not to be unexpected due to the restrictions placed on probe set design. However, it is expected that those probes mapping to multiple locations would not be from the _at class of probes.

To determine the reliability of these probes with the fluctuation of unknown transcripts, those probes that map with 100% identity to two or more locations in the genome were considered. While these probes typically represent less than 10% of the total number of probes for a given GeneChip®, their classification could be important in detecting cross hybridization. One might expect that the greatest percentage of these would be within the _x_at and _s_at classes. However, as Table 5 shows, the larger genomes actually contain the greatest percentage in the _at and _a_at classes, with anywhere from 18% (S. cerevisiae) to 91% (R. norvegicus) of the probes matching multiple locations belonging to the _at class. In addition, a small number of MM probes map to the genome as well. To better understand the effects this small set of MM probes might have on gene expression, we further reduced this to a smaller subset where the mapping was within exon regions. For these probes, we analyzed their signal intensities from random samples compared to the overall distribution of PM and MM intensities, and the distribution of PM and MM intensities within the corresponding exonic sequences (Figure 1). As these plots indicate, MM probes mapping within exonic regions closely follow the expression density of PM probes mapping within exonic regions, and are significantly shifted from the overall expression profiles of MM probes. These results suggest that while the number of these probes is small, they offer significant information that should not be ignored, and furthermore, can confound analyses where MM data is incorporated.

Table 5. Probe set classification of probes perfectly matching multiple genomic locations.

Figure 1. Density profile of probe intensities (log2). PM: perfect match, MM: mismatch. mm.all: background MM intensities; pm.all: background PM intensities; mm.exon: intensities of MM probes in exonic regions; pm.exon: intensities of PM probes in exonic regions.

As some of these MM probes may bind to transcripts, we further considered those MM probes that uniquely mapped to exons (irrespective of whether the corresponding PM probe mapped zero, one or multiple times to exons or the full genome), examining the differences in signal intensity between the MM and its associated PM. In many cases there is a significant negative difference in the expression level of the PM-MM pair (an example is shown in Figures 2 and 3).

Figure 2. Density of MM and PM probe set intensities not including the PM-MM pair that had a large negative difference. Intensities from zebrafish probeset Dr.5545.1.S1_at, in GEO sample GSM604808.CEL.gz.

Figure 3. Square root transformed intensities for each PM-MM pair. The negative difference pair is at the extreme right end of the figure. Intensities from zebrafish probeset Dr.5545.1.S1_at, in GEO sample GSM604808.CEL.gz.

If these MM probes are grouped instead with the other probes within the transcriptional region for which they uniquely match (we have renamed these probes as “true match” ™ probes since they truly match the region in the genome), there is a much better association between the probe intensities, as shown in Figure 4.

Figure 4. Plot of probe set intensities for zebrafish where the TM probes overlap with the same TMmm probe in Figure 3 Intensities from zebrafish probeset Dr.5545.1.S1_at, in GEO sample GSM604808.CEL.gz.

Further analysis was performed to test the correlation of the TM probes with the expression levels of both the annotated probe group MM probes and with the TM-mapped transcript probes (Figure 5). The box plot in Figure 5 clearly indicates that the TM intensities more closely correlate with those from the group based on mapping to the same exon.

Figure 5. Box plot of correlations of the TMmm with MM intensities of annotated probe set (red, MM) and TM intensities of custom probe sets based on shared mapping to exons (blue, TM)

To determine if the observed difference in the correlations from Figure 5 is due to measurement of different mRNA entities, we considered the MM probe both within its annotated location as well as within the new mapped location (TMmm). The intensity of the MM probe was compared with the intensity of its corresponding neighbor probes (MM probes for the annotated location; PM probes for the new mapped location). An average correlation value between intensities was calculated on a per-exon probe basis. The resulting correlations are summarized in Table 6.

What is interesting is that with few exceptions, the transcripts and genes being measured by the probe sets are the same, implying that the TMmm probe aligns to the same gene as its complimentary PM probe. Upon further examination it appears that many of the PM complements of the TMmm do not align to the genome at all (data not shown). One possibility is that these probes are in regions that have seen changes in the reference sequence over the years, or that the original sequencing of the ESTs used to design the probe sets was of poor quality.

Effects of Individual Variation

To gain an understanding of the effect of individual variation, the unique mapping of PM and MM probes to five distinct human genome assemblies was analyzed (Table 7). Four of the five projects have roughly the same number of uniquely mapped PM probes (within 2% variation). The fifth project (BGI) provides an exception to this trend. While there are a number of potential explanations for this (including sequence and assembly quality and coverage of the sequencing), one potential feature to be considered is the fact that this sequencing project involves the sequencing of an African individual, and it is the only project not to have a large component of the library consisting of Caucasian individuals.

Table 7. Number of probes mapping uniquely to individual human genomes.

While there is a large agreement for the number of probes, we also checked if the probes represented were consistent among all of the projects. A Venn diagram depicting the number of overlapping perfectly matching probes is given in Figure 6. As can be seen from this figure, a total of 422279 probes uniquely map for all five assemblies. Of these, 422118 are perfect match probes, indicating that 70% of the HGU133APlus2.0 perfect match probes are reliable in terms of their mapping to the genome for these assemblies. One of the interesting results is that there are 161 shared perfectly matching mismatch probes. Of these, 24 fall within RefSeq annotated exonic regions (results not shown), with 16 of the 24 showing higher correlation in the TMmm assignments calculated in Table 6.

Figure 6. Venn diagram of overlapping perfectly matching Affymetrix® HGU133A Plus2 probes to each of the five human genome assemblies.

Conclusion

MM probes are theoretically designed to capture background and non-specific binding. Alignment of the MM probes to the genome shows that in a very small percentage of cases, MM probes align uniquely to the genome in transcribed regions. Signal from these probes should be useful for quantifying true transcriptional events rather than for PM signal adjustment.

In addition, current custom CDF generation workflows ignore the MM probes during the probe alignment process. Given that some MM probes align to reference genomes, they should be considered for inclusion when creating custom CDFs. The utility of the probes may be limited due to variation among individuals.

ACKNOWLEDGEMENTS

This work was partially funded by National Institutes of Health (NIH) grant 8P20GM103436-12. Its contents are solely the responsibility of the authors and do not represent the official views of NIH or the National Institute of General Medical Sciences.

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RECREATION OF RESULTS

All of the necessary code to regenerate this work is hosted at https://github.com/rmflight/affymm. To recreate this html document, you need to run:

knit2html("flightetal_draft.Rmd", "flightetal_draft.html")

Alternatively use the Knit HTML button in RStudio v0.97 or newer. This document was generated using R version 2.15.0 (2012-03-30). The following information about packages used is also supplied:

sessionInfo()

R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] GenomicRanges_1.8.13    IRanges_1.14.4         
 [3] hgu133plus2probe_2.10.0 hgu133plus2.db_2.7.1   
 [5] org.Hs.eg.db_2.7.1      RSQLite_0.11.2         
 [7] DBI_0.2-5               AnnotationDbi_1.18.3   
 [9] Biobase_2.16.0          BiocGenerics_0.2.0     
[11] VennDiagram_1.5.1       plyr_1.7.1             
[13] ggplot2_0.9.2.1         knitr_0.8.1            

loaded via a namespace (and not attached):
 [1] colorspace_1.1-1   dichromat_1.2-4    digest_0.5.2      
 [4] evaluate_0.4.2     formatR_0.6        gtable_0.1.1      
 [7] labeling_0.1       MASS_7.3-21        memoise_0.1       
[10] munsell_0.4        proto_0.3-9.2      RColorBrewer_1.0-5
[13] reshape2_1.2.1     scales_0.2.2       stats4_2.15.0     
[16] stringr_0.6.1      tools_2.15.0