# Cross-Chip Probe Matching Tool: A Web-Based Tool for Linking Microarray Probes within and across Plant Species

Authors: Ruchi Ghanekar; Vinodh Srinivasasainagendra; Grier P. Page
Journal: International Journal of Plant Genomics
 (2008)

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## Abstract

The CCPMT is a free, web-based tool that allows plant investigators to rapidly determine if a given gene is present across various microarray platforms, which, of a list of genes, is present on array(s), and which gene a probe or probe set queries and vice versa, and to compare and contrast the gene contents of arrays. The CCPMT also maps a probe or probe sets to a gene or genes within and across species, and permits the mapping of the entire content from one array to another. By using the CCPMT, investigators will have a better understanding of the contents of arrays, a better ability to link data between experiments, ability to conduct meta-analysis and combine datasets, and an increased ability to conduct data mining projects.


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## Body

## 1. Introduction

Microarrays are
an incredibly  powerful technology that enables the
rapid and  relatively
accurate measurement  of thousands  of genes
in a single sample. Many different
microarray platforms  have been developed and
each has somewhat  different content
and format. One key difference is the type of probe used to query a gene
expression; some platforms use a single probe, and others use many probes. The
probes may be short (25 base pairs) oligonucleotides (Affymetrix and NimbleGen
arrays), long (50–70 bp)
oligonucleotides (Operon, Agilent, CATMA), or cDNA clones (AFGC arrays). Each
of the formats has its advantages and disadvantages as well as its proponents
and opponents. One thing on which everybody agrees is that arrays will be a
part of the experimental techniques of plant biologists for years to come.Since there are
many microarray platforms even  within a single species, different investigators
may use different platforms to try to address similar or complementary
experimental questions or data may  be
collected across types using different platforms. Also, the large number of
datasets that sets in the public domain allow can be used for data mining or
meta-analysis if the elements can be connected. However, it is difficult to
compare and combine the results due to the difficultly in matching probes across
arrays with the genes, or even to determine if a given gene is on a given platform.
To make matters worse, while the probe sequences on an array are constant, the
genome annotation and gene models are not, and homologous genes may have
different names across species. As a result, matching probes across arrays is
continually evolving and needs continuing updating.Investigators have long
realized the problem of linking probes across platforms; as a result, several
tools have been developed. These include Keck ARray Manager and
Annotator (KARMA) [1], RESOURCERER [2], and GeneSeer
[3]. Our tool has several advantages over the other tools for several reasons.
None of the other tools allows investigators to query for genes within a
microarray platform nor do the other tools allow queries by Arabidopsis Genome Initiative (AGI) annotation IDs or by TIGR tentative consensus (TC) gene
IDs. Furthermore, our tool sends the results to the investigators by email as
well as a web-based report making results’ tracking and storage easier. More
importantly for plant researchers, only RESOURCERER has any provision for the
linking of plant array data, but it has fewer array types.We developed the
CCPMT to enable investigators to rapidly determine (1) if a given gene is
present across many types of array platforms within and across species, (2)
which, of a list of genes, is present on array(s), and (3) which gene a probe
or probe set queries. The CCPMT also maps a probe set or probe sets to a gene
or genes within and across species, and permits the mapping of the contents
from one array to another, both within and across species.The CCPMT is the first tool exclusively designed for linking probes from
plant microarrays within and across microarray platforms and species. A web-based
tool, CCPMT, helps investigators query for annotations at probe level with
probe set IDs or even at gene level with gene identifiers such as AGI, EGO [4],
and TC IDs. In CCPMT, an investigator can enter either individual or multiple
probe set or gene identifiers (separated by commas) in the textbox to query the
CCPMT database. Checkboxes for microarray vendors provide the option of
selecting multiple arrays while querying the CCPMT database. CCPMT also offers
the flexibility to carry out a one-to-one comparison of microarrays. Results
are displayed immediately in the web browser and are also sent through email in
a csv∗ file format.CCPMT has a
flexible database design, and in the immediate future additional plant arrays
will be added to the database; we will revise the underlying annotation and
mapping for the probes based upon new genomic information.By using the
CCPMT, investigators will have a better understanding of the contents of arrays,
a better ability to link data between  experiments,
plus
the ability to more easily conduct data mining projects.


## 2. Methods

### 2.1. Arrays Selected for Initial Analysis

Initially we focused upon
microarrays with diverse probe types (short and long oligos as well as cDNA)
and for bothPoplar and Arabidopsis. Poplar and Arabidopsis were chosen due to both having completely sequenced genomes and being
relatively closely related species. The Arabidopsis arrays as tools are the
Affymetrix Arabidopsis genome (8 K) commonly referred to as AG,
Affymetrix Arabidopsis genome ATH1-121501 (25 K) commonly referred to as
ATH1, Agilent Arabidopsis 2 Oligo Microarray (V2) G4136B, Arabidopsis Functional
Genomics Consortium (AFGC) array, Complete Arabidopsis Transcriptome
MicroArray (CATMA) array, Operon Arabidopsis Genome Oligo Set Version 3.0, and Affymetrix Poplar Genome Array. The array that we are calling AFGC actually
represents all cDNA clones used in all of the AFGC arrays including the 11 k,
13 k, and 16 k  arrays.


### 2.2. Arabidopsis Data Preprocessing

We obtained the probe set ID, the vendor’s corresponding mapping to AGI ID (for Arabidopsis arrays), and the nucleotide sequences of the probe sets (Table1) directly from the vendors.Table 1
Web pages from where plant microarray data were downloaded.
Probe sequence file locationVendor-provided annotation file
locationAffymetrix AGhttp://www.affymetrix.com/support/technical/byproduct.affx?product=atgenome1http://www.affymetrix.com/support/technical/ byproduct.affx?product=atgenome1Affymetrix ATH1http://www.affymetrix.com/support/technical/ byproduct.affx?product=arabhttp://www.affymetrix.com/support/technical/ byproduct.affx?product=arabOperonhttp://omad.operon.com/download/index.phphttp://omad.operon.com/download/index.phpCATMAftp://ftp.arabidopsis.org/home/tair/Microarrays/CATMA/ftp://ftp.arabidopsis.org/home/tair/Microarrays/CATMA/AFGCftp://ftp.arabidopsis.org/home/tair/Microarrays/AFGC/ftp://ftp.arabidopsis.org/home/tair/ Microarrays/AFGC/AgilentNA (do not provide sequence files)http://www.chem.agilent.com/Scripts/ PDS.asp?lPage=37068AffymetrixPoplar Genome Arrayhttp://www.affymetrix.com/support/technical/ byproduct.affx?product=poplarhttp://www.affymetrix.com/support/technical/ byproduct.affx?product=poplarIn the case ofArabidopsis, all
vendors provided the mappings between their probe sets and the corresponding
AGI gene identifiers. However, due to evolving genome annotation, we derived a
new set of mappings between the probe sets and the corresponding AGI IDs. The
steps of the process are  illustrated in Figure 1. The mapping was accomplished
using the NCBI blastn [5] program. Blastn compares
a nucleotide query sequence against a nucleotide sequence database. We
used two different databases for blastn analysis. For the Affymetrix and Operon
probe sequences, which do not contain introns, the AGI CDS database at TAIR was
used as the sequence database due to the lack of introns and the UTRs in this
database. The AGI CDS dataset is based on the TAIR6.0 release version, and was
released in November 2005. For the AFGC
and CATMA arrays, which do contain some intronic and UTR sequences, the AGI Transcripts dataset was used. The AGI
Transcripts dataset includes all of the coding sequences from Arabidopsis, as well as containing the UTRs. Neither database contained intronic sequence.
The AGI Transcripts dataset  used the TAIR6.0 release version and was released
in November 2005. The blastn expected  value and percent identity cut-off were
10−4    and 98%, respectively.Figure 1
CCPMTArabidopsis BLAST
workflow. The workflow in CCPMT to get the probe set to AGI mappings is shown.


### 2.3. Poplar Data Preprocessing

About 27%
of thePoplar sequence have significant homology to Arabidopsis protein-coding sequences [6]
and have been sequenced. Unlike Arabidopsis, Poplar does not have a
universal gene annotation ID; so in CCPMT Poplar, probe sets are mapped within
the species using the TIGR TC IDs and across plant species using the EGO
database. The Poplar target sequences were sequence-aligned with the
TIGR Poplar TC dataset using the blastn program as shown in Figure 2.
The blastn expected value and percent identity cut-off were 10−4 and
98%, respectively. TIGR also provides a file with a mapping of the EGO ID and
the corresponding TCs for all species. From this file, the mappings between EGO
IDs and the corresponding Arabidopsis and Poplar TCs were parsed.
The mapping of the TC to EGOs was assumed to be correct. In the future, any
plant species with genes mapping to an EGO ID can be easily incorporated into
CCPMT. Mapping the Arabidopsis TCs to their corresponding AGI IDs was achieved by using the Arabidopsis TC sequences (TIGR provides this file) and sequence-aligning with the TAIR “AGI
Transcripts” dataset using blastn. Based on the cut-offs used there is the one-to-many
mapping at several stages. A probe set can map to multiple genes, and multiple
probe sets can map to  one gene (Table 2).Table 2
Comparing
microarray vendor and CCPMT  mappings.
Type of matchAffymetrix
AGAffymetrix
ATH1OperonCATMAAFGCNumber of probes per array type829722810299542457619108Nil entries from vendor
(no mapping for these probes)14125093629692823Absent-vendor; present-blast00001Present-vendor; absent-blast8509302335299010952Many-vendor; one-blast124584030117One-vendor; many-blast338896480408368Exact match69322019326138195516413aPercentage of the vendor mapping numbers84%89%87%80%34%Figure 2
Poplar-Arabidopsis mapping. The above workflow explains the steps
that were undertaken while mapping the Affymetrix Poplar probe set ID
with the Arabidopsis probe set ID. TIGR EGO ID was used to go across
species during mapping.As an  example, Figure3 illustrates the mapping of the Affymetrix Poplar Genome Array with the
Affymetrix AG and Affymetrix ATH1 arrays; similar processes are used for the
other arrays. Table 3 contains the number of matches that were found between
all possible matches among arrays.Table 3
Summary table of the number of
probes that are linked between the various arrays currently in the CCPMT from
the array in row to the arrays in columns. The above and below diagonal
elements are slightly different for the methods we used such as Blasn, and
percent identity is not always reflexive.
Affymetrix
AGAffymetrix
ATH1AFGCAgilentCATMAOperonAffymetrixPoplar Genome ArrayAffymetrix
AG—7828121707018719383617744Affymetrix ATH17827—3006619188205212463617279AFGC1217130066—29622260703050917793Agilent70181918829622—185632137116913CATMA7192205212607018561—2308216378Operon836224636305092137123081—17505AffymetrixPoplar Genome Array77441727917793169121637817504—Workflow for the
mapping between AffymetrixPoplar, Affymetrix AG, and Affymetrix ATH1
arrays.


### 2.4. The CCPMT Application

The  CCPMT
(http://www.ssg.uab.edu/ccpmt/) is composed of three
pieces, namely, web pages (front end), core methods, and database (back end). The
CCPMT web pages are written in JSP. Once the user hits the submit button, all
of the data that have been entered are sent to the core code of Java servlets. The
servlets act as the core methods that process the information received from the
JSP pages and query the database. MySQL is used as the back-end database to
store the microarray mappings. The code
underlying the CCPMT is available from the corresponding author by request.


### 2.5. Using
the CCPMT

The CCPMT is designed to be flexible
and to allow for linking probes across arrays from a variety of starting data. CCPMT
can be queried either at the probe set level or with identifiers such as the
probe set IDs, AGI IDs, TIGR EGO IDs, or TC IDs, and output can be and is
returned in these formats as well. As CCPMT is a web application, users can
type or paste their queries in a textbox and, upon submission of the queries,
the results are displayed in a browser-friendly format. One can also compare
entire arrays by selecting the input array and the output array from the
drop-down  menu.


### 2.6. Example of the Use of CCPMT

We illustrate the utility of the
CCPMT via mapping the probe set 244904_at that is found on the Affymetrix AG array
to determine  which probe sets on the ATH1 array query the same gene. Step 1 (illustrated
in Figure S1 in Supplementary Material available online
at doi:10.1155/2008/451327) shows that the user wants to map the input data using
Affymetrix probe set IDs. In addition, users’ email address is entered so that
the results can also be sent as an attachment in comma-separated file format. The
next step (see Figure S2) is to enter the  probe set(s), 244904_at in this case,
and the species of the probe set, and to indicate which
arrays to find homologous probe sets (in this example, Affymetrix AG and
Affymetrix ATH1 arrays). The results are then displayed in Figure S3 which
shows that the probe set 244904_at was mapped to 244922_s_at and 244923_s_at through
the respective AGI IDs and that they map to AT2G07674.


## 2.1. Arrays Selected for Initial Analysis

Initially we focused upon
microarrays with diverse probe types (short and long oligos as well as cDNA)
and for bothPoplar and Arabidopsis. Poplar and Arabidopsis were chosen due to both having completely sequenced genomes and being
relatively closely related species. The Arabidopsis arrays as tools are the
Affymetrix Arabidopsis genome (8 K) commonly referred to as AG,
Affymetrix Arabidopsis genome ATH1-121501 (25 K) commonly referred to as
ATH1, Agilent Arabidopsis 2 Oligo Microarray (V2) G4136B, Arabidopsis Functional
Genomics Consortium (AFGC) array, Complete Arabidopsis Transcriptome
MicroArray (CATMA) array, Operon Arabidopsis Genome Oligo Set Version 3.0, and Affymetrix Poplar Genome Array. The array that we are calling AFGC actually
represents all cDNA clones used in all of the AFGC arrays including the 11 k,
13 k, and 16 k  arrays.


## 2.2. Arabidopsis Data Preprocessing

We obtained the probe set ID, the vendor’s corresponding mapping to AGI ID (for Arabidopsis arrays), and the nucleotide sequences of the probe sets (Table1) directly from the vendors.Table 1
Web pages from where plant microarray data were downloaded.
Probe sequence file locationVendor-provided annotation file
locationAffymetrix AGhttp://www.affymetrix.com/support/technical/byproduct.affx?product=atgenome1http://www.affymetrix.com/support/technical/ byproduct.affx?product=atgenome1Affymetrix ATH1http://www.affymetrix.com/support/technical/ byproduct.affx?product=arabhttp://www.affymetrix.com/support/technical/ byproduct.affx?product=arabOperonhttp://omad.operon.com/download/index.phphttp://omad.operon.com/download/index.phpCATMAftp://ftp.arabidopsis.org/home/tair/Microarrays/CATMA/ftp://ftp.arabidopsis.org/home/tair/Microarrays/CATMA/AFGCftp://ftp.arabidopsis.org/home/tair/Microarrays/AFGC/ftp://ftp.arabidopsis.org/home/tair/ Microarrays/AFGC/AgilentNA (do not provide sequence files)http://www.chem.agilent.com/Scripts/ PDS.asp?lPage=37068AffymetrixPoplar Genome Arrayhttp://www.affymetrix.com/support/technical/ byproduct.affx?product=poplarhttp://www.affymetrix.com/support/technical/ byproduct.affx?product=poplarIn the case ofArabidopsis, all
vendors provided the mappings between their probe sets and the corresponding
AGI gene identifiers. However, due to evolving genome annotation, we derived a
new set of mappings between the probe sets and the corresponding AGI IDs. The
steps of the process are  illustrated in Figure 1. The mapping was accomplished
using the NCBI blastn [5] program. Blastn compares
a nucleotide query sequence against a nucleotide sequence database. We
used two different databases for blastn analysis. For the Affymetrix and Operon
probe sequences, which do not contain introns, the AGI CDS database at TAIR was
used as the sequence database due to the lack of introns and the UTRs in this
database. The AGI CDS dataset is based on the TAIR6.0 release version, and was
released in November 2005. For the AFGC
and CATMA arrays, which do contain some intronic and UTR sequences, the AGI Transcripts dataset was used. The AGI
Transcripts dataset includes all of the coding sequences from Arabidopsis, as well as containing the UTRs. Neither database contained intronic sequence.
The AGI Transcripts dataset  used the TAIR6.0 release version and was released
in November 2005. The blastn expected  value and percent identity cut-off were
10−4    and 98%, respectively.Figure 1
CCPMTArabidopsis BLAST
workflow. The workflow in CCPMT to get the probe set to AGI mappings is shown.


## 2.3. Poplar Data Preprocessing

About 27%
of thePoplar sequence have significant homology to Arabidopsis protein-coding sequences [6]
and have been sequenced. Unlike Arabidopsis, Poplar does not have a
universal gene annotation ID; so in CCPMT Poplar, probe sets are mapped within
the species using the TIGR TC IDs and across plant species using the EGO
database. The Poplar target sequences were sequence-aligned with the
TIGR Poplar TC dataset using the blastn program as shown in Figure 2.
The blastn expected value and percent identity cut-off were 10−4 and
98%, respectively. TIGR also provides a file with a mapping of the EGO ID and
the corresponding TCs for all species. From this file, the mappings between EGO
IDs and the corresponding Arabidopsis and Poplar TCs were parsed.
The mapping of the TC to EGOs was assumed to be correct. In the future, any
plant species with genes mapping to an EGO ID can be easily incorporated into
CCPMT. Mapping the Arabidopsis TCs to their corresponding AGI IDs was achieved by using the Arabidopsis TC sequences (TIGR provides this file) and sequence-aligning with the TAIR “AGI
Transcripts” dataset using blastn. Based on the cut-offs used there is the one-to-many
mapping at several stages. A probe set can map to multiple genes, and multiple
probe sets can map to  one gene (Table 2).Table 2
Comparing
microarray vendor and CCPMT  mappings.
Type of matchAffymetrix
AGAffymetrix
ATH1OperonCATMAAFGCNumber of probes per array type829722810299542457619108Nil entries from vendor
(no mapping for these probes)14125093629692823Absent-vendor; present-blast00001Present-vendor; absent-blast8509302335299010952Many-vendor; one-blast124584030117One-vendor; many-blast338896480408368Exact match69322019326138195516413aPercentage of the vendor mapping numbers84%89%87%80%34%Figure 2
Poplar-Arabidopsis mapping. The above workflow explains the steps
that were undertaken while mapping the Affymetrix Poplar probe set ID
with the Arabidopsis probe set ID. TIGR EGO ID was used to go across
species during mapping.As an  example, Figure3 illustrates the mapping of the Affymetrix Poplar Genome Array with the
Affymetrix AG and Affymetrix ATH1 arrays; similar processes are used for the
other arrays. Table 3 contains the number of matches that were found between
all possible matches among arrays.Table 3
Summary table of the number of
probes that are linked between the various arrays currently in the CCPMT from
the array in row to the arrays in columns. The above and below diagonal
elements are slightly different for the methods we used such as Blasn, and
percent identity is not always reflexive.
Affymetrix
AGAffymetrix
ATH1AFGCAgilentCATMAOperonAffymetrixPoplar Genome ArrayAffymetrix
AG—7828121707018719383617744Affymetrix ATH17827—3006619188205212463617279AFGC1217130066—29622260703050917793Agilent70181918829622—185632137116913CATMA7192205212607018561—2308216378Operon836224636305092137123081—17505AffymetrixPoplar Genome Array77441727917793169121637817504—Workflow for the
mapping between AffymetrixPoplar, Affymetrix AG, and Affymetrix ATH1
arrays.


## 2.4. The CCPMT Application

The  CCPMT
(http://www.ssg.uab.edu/ccpmt/) is composed of three
pieces, namely, web pages (front end), core methods, and database (back end). The
CCPMT web pages are written in JSP. Once the user hits the submit button, all
of the data that have been entered are sent to the core code of Java servlets. The
servlets act as the core methods that process the information received from the
JSP pages and query the database. MySQL is used as the back-end database to
store the microarray mappings. The code
underlying the CCPMT is available from the corresponding author by request.


## 2.5. Using
the CCPMT

The CCPMT is designed to be flexible
and to allow for linking probes across arrays from a variety of starting data. CCPMT
can be queried either at the probe set level or with identifiers such as the
probe set IDs, AGI IDs, TIGR EGO IDs, or TC IDs, and output can be and is
returned in these formats as well. As CCPMT is a web application, users can
type or paste their queries in a textbox and, upon submission of the queries,
the results are displayed in a browser-friendly format. One can also compare
entire arrays by selecting the input array and the output array from the
drop-down  menu.


## 2.6. Example of the Use of CCPMT

We illustrate the utility of the
CCPMT via mapping the probe set 244904_at that is found on the Affymetrix AG array
to determine  which probe sets on the ATH1 array query the same gene. Step 1 (illustrated
in Figure S1 in Supplementary Material available online
at doi:10.1155/2008/451327) shows that the user wants to map the input data using
Affymetrix probe set IDs. In addition, users’ email address is entered so that
the results can also be sent as an attachment in comma-separated file format. The
next step (see Figure S2) is to enter the  probe set(s), 244904_at in this case,
and the species of the probe set, and to indicate which
arrays to find homologous probe sets (in this example, Affymetrix AG and
Affymetrix ATH1 arrays). The results are then displayed in Figure S3 which
shows that the probe set 244904_at was mapped to 244922_s_at and 244923_s_at through
the respective AGI IDs and that they map to AT2G07674.


## 3. Discussion

Microarrays are gaining popularity
in plant research. In addition, the requirement of many journals to deposit
microarray data into public databases has made large amounts of data available
for other investigators to use. But because there are a large number of arrays
and array types, it can be difficult to compare data across datasets. We
developed the CCPMT to allow investigators to identify common elements between
databases rapidly and accurately.While most
vendors provide  some mapping of probes to genes, in many cases the annotation
is out of data or the companies use different standards for mapping. In some
cases, there is considerable difference between our mapping and those provided
with the arrays. This is due to at least three reasons. The first is that sequence,
gene models, and annotation, especially  for the incompletely sequenced genomes,
can change rapidly. As a result, the provided annotation may be out of date.
For example, data for CATMA and AFGC, obtained with TAIR atftp://ftp.arabidopsis.org/home/tair/Microarrays/, had a timestamp of January
2006, but the FASTA file format has a timestamp of April 2004. The second reason for differences would be the
choice of cut-off for mapping. We used >98% and E score of less than 10−4 for all but the AFGC arrays. Our
choice of >98% is  debatable, and somewhat different answers are obtained if
other values are used; 98% may  identify some paralogous genes, especially
across species. It has not been conclusively established what level of sequence
similarity is needed between a gene and a probe set for efficient binding. It
is known that a single-base-pair difference in a short oligo can (with >50%
of the time depending on the position of the SNP) destroy most binding. But
since Affymetrix arrays usually have 11 sets of short oligos, the nonbinding of
a single probe may or may not affect the overall RNA quantitation [7]. Long
oligos bind relatively well with a few (1–3 bp)
differences, but there is usually no redundancy of the addition of probes. cDNA clones
can be quite long and only a portion of the sequence needs to be homologous for
binding. A third source of difference
may result from the choice of common genes. We used the TIGR EGO, but the NCBI HomoloGene (http://www.ncbi.nlm.nih.gov/sites/entrez?db=homologene)
also identifies homologous genes across species. Unfortunately, these databases
give slightly different mapping. We have used TIGR EGO database as it has more
plant sequence data and has plant biologists devoted to curating the databases,
as opposed to HomoloGene which is mammal-centric. Thus, the choice we made
about cut-offs is conservative, but we have probably missed some probes with
lower homology that actually do bind certain RNAs, and many others identify
paralogous genes. As a result of these issues, our mapping is different from
those provided by the vendor. The highest overlap is between the mapping
provided by Affymetrix and the CCPMT mapping for the Affymetrix ATH1 array at
89%, while the AFGC has the lowest overlap at about 66%.We think that the
function allowing direct comparison of complete arrays is very useful for
several reasons. One of the reasons why we developed the CCPMT was to allow
coexpression analysis across arrays and species. This mapping in the CCPMT will
be the basis of our next additions to CressExpress (http://www.cressexpress.org/), and others may
use this as well for similar projects. Data from experiments that are often
collected across time and  different array  platforms are used, which requires
the mapping of probes across array platforms. This ability will be greatly amplified by the
ability of the CCPMT to map data across platforms.The annotation
and sequence for genes as well as gene models are continuing to evolve,
especially as additional species are sequenced. We have set up the CCPMT to
allow for us to rapidly change the various portions of the database and mapping
as data change. We plan to revise the CCPMT based upon new genomic information.CCPMT currently has sixArabidopsis microarray arrays and one Poplar microarray. The tool
was designed in such a way that one can easily incorporate a new microarray
vendor for the current plant species as well as for new plant species.  In the near future,
we will rule out mapping for all
Affymetrix-provided arrays for plant species, as well as those long oligo
arrays from Operon and Agilent.



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*Source: 451327-2008-10-21.xml*