# MaizeGDB: The Maize Model Organism Database for  Basic, Translational, and Applied Research

Authors: Carolyn J. Lawrence; Lisa C. Harper; Mary L. Schaeffer; Taner Z. Sen; Trent E. Seigfried; Darwin A. Campbell
Journal: International Journal of Plant Genomics
 (2008)

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## Abstract

In 2001 maize became the number one production crop in the world with the Food and Agriculture Organization of the United Nations reporting over 614 million tonnes produced. Its success is due to the high productivity per acre in tandem with a wide variety of commercial uses. Not only is maize an excellent source of food, feed, and fuel, but also	 its by-products are used in the production of various commercial products.  Maize's unparalleled success in agriculture stems from basic research, the outcomes of which drive breeding and product development.  In order for basic, translational, and applied researchers to benefit from others' investigations, newly generated data must be made freely and easily accessible.  MaizeGDB is the maize research community's central repository for genetics and genomics information.  The overall goals of MaizeGDB are to facilitate access to the outcomes of maize research by integrating new maize data into the database and to support the maize research community by coordinating group activities.


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## Body

## 1. Introduction

Maize (Zeamays L.) is a species that encompasses
the subspecies mays (commonly called “corn” in the US)
as well as the various teosintes that gave rise to modern maize. Maize is an important crop: not only is it one of the most abundant sources of food and feed for
people and livestock the world over, it is also an important component of many
industrial products. Maize byproducts
are present in, for example, glue, paint, insecticides, toothpaste, rubber
tires, rayon, and molded plastics, among others. Maize is also currently the nation’s major
source of ethanol, a major biofuel that is more environmentally friendly than
gasoline and that may be a more economical fuel alternative in the long
run. Although it is unlikely that
ethanol production from maize directly will be sustainable long-term, maize’s
suitability to serve as a model organism for developing fuelstock grasses is
apparent [1]. Indeed, in addition to its
value as a commodity, maize has been a premiere model organism for biological
research for over 100 years. Many
seminal scientific discoveries have first been shown in maize, such as the
identification [2] and cloning [3] of transposable elements, the correlation between cytological and
genetic crossing over [4], and the discovery of epigenetic phenomena [5]. These exceptional
characteristics of maize set this amazing plant apart: no other species serves as both a commodity
and a leading model for basic research.Today, with the accelerated generation of maize genetic
and genomic information, the need for a centralized biological data repository
is critical. MaizeGDB (theMaizeGenetics and genomics Data Base [6]) (http://www.maizegdb.org/)
is the Model Organism Database (MOD) for maize.
Stored at MaizeGDB is comprehensive information on loci (genes and other
genetically defined genomic regions including QTL), variations (alleles and
other sorts of polymorphisms), stocks, molecular markers and probes, sequences,
gene product information, phenotypic images and descriptions, metabolic pathway
information, reference data, and contact information for maize
researchers. Described in the results and discussion section are example workflows that
could be followed by researchers to utilize the MaizeGDB resource for their
research. Other long-term resources
serving maize data include Gramene (http://www.gramene.org/) [7], which
specializes in grass comparative genomics, and GRIN (the Germplasm Resources
Information Network; http://www.ars-grin.gov/npgs/), which provides access to
the National Plant Germplasm System’s germplasm stocks and related breeding
data. MaizeGDB makes an effort to guide
researchers to these resources via context-sensitive linkages rather than
duplicating data, though some data are shared simply to allow for the
context-sensitive linkages to be created.
This reduces duplication in effort and allows personnel skilled in
comparative genomics and germplasm conservation/plant breeding to interact with
maize researchers directly via Gramene and GRIN, respectively.In addition to
storing and making maize data available, the MaizeGDB team also provides
services to the community of maize researchers and offers technical support for
the Maize Genetics Executive Committee and the Annual Maize Genetics
Conference. Also available at the
MaizeGDB website, as a service to the maize research community, are bulletin
boards for news items, information of interest to cooperators, lists of
websites for projects that focus on the scientific study of maize, the
Editorial Board’s recommended reading list, and educational outreach items.The genetic and
genomic data as well as community-related information maintained by MaizeGDB
are highly utilized: MaizeGDB averages 8620 visitors (based on unique Internet
Protocol or IP addresses) and over 160 000 page impressions per month (July
2007 to June 2008). In addition,
MaizeGDB came in fifth
out of 170 in a National Plant Genome Initiative Grantees poll in which lead
principal investigators reported most useful websites for their research [8].


## 2. Materials and Methods

### 2.1. Kinds of Data in the Database that Link Genetic and Genome Sequence Information

MaizeGDB is the primary repository for the major genetic and
cytogenetic maps and includes details about genes, mutants, QTL (quantitative
trait loci), and molecular markers including 2500 RFLPs (restriction fragment
length polymorphisms), 4625 SSRs (simple sequence repeats), 363 SNP (single
nucleotide polymorphisms), 2500 indels (insertion/deletion sites), and 10 644 overgos (overlapping oligonucleotides). These data
are described using 1.27 millions synonyms, 42 000 primer sequences, 16 394 raw
scores from mapping based upon 16 panels of stocks, and 323 313 links to
GenBank [9] accessions. GenBank
accessions form the links between the genetic position on a chromosome, the
sequence records at MaizeGDB, and the EST (expressed sequence tag) and GSS
(genome survey sequence) contig assemblies at PlantGDB [10] and Dana Farber (The Gene Indices at http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=maize,
previously at TIGR [11]). All of the 3 520 247
sequences in MaizeGDB are accessible by BLAST [12] and can be filtered to report only mapped loci, including any
SSRs and overgos that may not be mapped genetically, but via BACs (bacterial
artificial chromosomes) in anchored contigs.The inclusion of the public
BAC FPC (Finger Print Contig) information [13] adds 439 449 BACs together with associated overgo, SSR, and RFLP
markers, which are used to assemble the contigs and to link contigs onto
genetic map coordinates. The order of
loci on the BAC contigs is represented by over 27 000 sequenced-based loci on
the IBM2 FPC057 maps (http://www.maizegdb.org/cgi-bin/displaymapresults.cgi?term=ibm2+fpc0507)
in MaizeGDB, by links to contigs at both the Arizona FPC site (http://www.genome.arizona.edu/) and the
genome sequencing project (http://www.maizesequence.org/). As the B73 genome sequence progresses, these
BAC sequences are added to MaizeGDB along with links to the sequencing project,
both from the BAC clones and from genetically mapped loci associated with a
BAC.The newest maps in MaizeGDB,
IBM SNP 2007 (http://www.maizegdb.org/cgi-bin/displaymapresults.cgi?term=ibm%20snp%202007),
are the first of a new generation of genetic maps from the Maize Diversity
Project (http://www.panzea.org/) kindly provided
pre-publication by Dr. Mike McMullen. The SNP loci on these maps are associated with allelic sequences from a
core set of maize and teosinte germplasm. Because the majority of the anticipated 1128 loci have been previously
mapped onto BAC clones [13, 14], these genetic maps tightly link sequence diversity to the B73
genome sequence.


### 2.2. Methods of Access, Environments, and the Database Back End

#### 2.2.1. The Production Web Interface

Maize researchers primarily access MaizeGDB through the series of interconnected Web
pages available athttp://www.maizegdb.org/
(see Figure 1). These web pages are
dynamically generated and are written in PHP (the recursive abbreviation for
PHP Hypertext Preprocessor [15])
and Perl [16]. Through this interface, each page shows
detailed information on a specific biological entity (such as a gene) as well
as basic information about data associated with it (genes are associated with
maps, phenotypes, and citations, among others). These additional data types are linked to the gene page, enabling quick
access to alternative data views. The
site also includes links to related resources at other databases; genes, for
example, are linked to Gramene [7].Figure 1
The MaizeGDB home page. The most commonly utilized search
functionality for MaizeGDB is the search bar (A), which is available within the
header of any MaizeGDB page. To browse
data and to search specific data types using specific limiters, the Data
Centers (B) are also quite useful. Also
available is a Bin Viewer (C), which allows for a view of lots of data types
within the context of their chromosomal location. To enable access to the Data Centers
and other displays of interest from any MaizeGDB page, a pull-down menu for
“Useful pages” (D) is accessible on the header of any MaizeGDB page. The footer of all MaizeGDB pages contains a
context-sensitive “feedback form” link (E).
Researchers use the feedback form to report errors, ask questions, and
to contact the MaizeGDB team directly.
For newcomers to the site, the MaizeGDB Tutorial (F) can help them to
get a jump start on how to use the site.One may access these individual data pages by using either (1) the
search bar located at the top right of every page (Figure1(A)), or (2) data
type-specific advanced querying tools (accessible via the “Data Centers” links;
Figure 1(B)) on the left side of the home page, or (3) the Bin Viewer tool
(Figure 1(C)), which is located in the left margin of the home page or via a
pull down labeled “Useful pages” (Figure 1(D)) accessible at the top of any
MaizeGDB page. These tools allow researchers
to easily find relevant data displays.MaizeGDB's method of data
delivery has three primary goals: placing information within the framework of
its scientific meaning, making this information available to the researcher
with minimal input (often only the relevant term), and requiring minimal effort
from the researcher to comprehend the data displays. By focusing on biological context and ease of
use as the primary focus of this interface (the “production” Web interface),
the database is intended to be intuitive to the researcher as their click
stream follows a logical path of biological associations. Up-to-date site usage statistics can be
accessed online athttp://www.maizegdb.org/usage/.


#### 2.2.2. Structure and Relationship of Environments: Production, Staging, and Test

The production Web interface, which most MaizeGDB users interact with, is only one component of the overall
MaizeGDB infrastructure (Figure2). The
data accessed by the production Web interface are typically updated on the
first Tuesday of each month. Prior to being in that Production Environment, the data are prepared for public
accessibility in a Staging Environment. In the Staging Environment, the most up-to-date information is
available, new data are added to the database, and existing data are updated
with new information. In addition to a
Web interface that appears identical to the one in the Production Environment,
the Staging Environment offers SQL (Structured Query Language) read-only access
to the community so that researchers interested in interacting with the data in
a more direct and customized manner can have access to the most up-to-date
information available. In addition, a Disaster Recovery system has been put
in place whereby the Curation Database is backed up in a compressed format to a
separate machine in Ames, Iowa daily.  Once weekly, the Ames file is copied to Columbia,
Missouri for off-site storage.Figure 2
Simplified infrastructure of MaizeGDB. The community of maize researchers can add
data to the database (downward-facing arrows from the uppermost yellow box) via
direct data deposition (upper left) and via a set of Community Curation Tools
that interacts with the Curation Database (upper center). Researchers are also allowed access to maize
data (upward-facing arrows from the lower dashed box) via a web interface that
can be accessed athttp://www.maizegdb.org/
(upper right) and by way of SQL access to the Curation Database, which houses
the most up-to-date data available (upper center). These functionalities are supported by two of
the three environments: Production and
Staging, respectively (upper dashed gold boxes). Available for use by MaizeGDB personnel to
facilitate data modeling and trial programming manipulations is a third
environment called Test (lower left dashed gold box), which is identical to the
Staging Environment. To ensure that the
most up-to-date copy of the database is backed up, a Disaster Recovery process
has been instituted (lower center dashed gold box) whereby a compressed copy of
the database is backed up to a separate machine in Ames, Iowa daily, and to a
server in Columbia, Missouri weekly.To aid in the modeling of new
types of data for inclusion in the MaizeGDB product and to enable programming
to be tried out in a safe place, a Test
Environment identical to the Staging Environment has been created. Note that three copies of the database
exist. While each environment and server
has a specific purpose, all are configured such that they could serve a backup
to each other. If any one server was to
fail, either of the other two could provide full, unrestricted data access and
site functionality. The curation
database is backed up on a daily basis and is available for download (http://goblin1.zool.iastate.edu/~oracle/)
for those who have Oracle Relational Database Management System (RDBMS)
installed locally.


#### 2.2.3. Curation

Also available within the Staging Environment are Community
Curation Tools to enable researchers to add small datasets to the database
directly, as well as a set of Professional Curation Tools developed by Dr.
Marty Sachs’ group at the Maize Genetics Cooperation-Stock Center in Urbana-Champaign [17]. Whereas the Community
Curation Tools have many safeguards to help researchers enter data step-wise
and with enforced field requirements, the Professional Curation Tools allow
MaizeGDB project members as well as Stock Center personnel to enter datasets in
a more stream-lined and powerful fashion with fewer integrity enforcement rules
(which slow down the data entry process considerably). It also should be noted that data added to
the database via the Community Curation Tools are first marked as
“Experimental” that must be “Activated” by professional curators at
MaizeGDB. This ensures that only quality information is made publicly accessible.
The availability of a Curation Web interface (within the Staging
Environment) enables researchers to view the data as they will appear once they
are uploaded to Production. Few
researchers (about 30 at present) have Community Curation accounts. To increase the use of these tools, training
sessions are being organized (see Section 2.3, below). If researchers wish to deposit complex or
large datasets, it would not be reasonable to enter the data via the Community
Curation Tools because those tools work via a “bottom-up” approach whereby the
records are (1) built based upon the most basic information included in the
dataset and (2) entered one record at a time (i.e., not in bulk). For complex or large datasets, researchers
are encouraged to submit data files to the curators at MaizeGDB. Those data are added to the database directly
by curators and the database administrator.


#### 2.2.4. Database Back End

Each environment’s server has
a perpetual license and is supported by Oracle RDBMS powered by2×2.0 GHz
Xeon processors, 4 GB of RAM, 5×73 GB Ultra 320 10 K RPM drives with Red Hat
Advanced Server 2.1 operating system installed. The curation database,
either partially or in its entirety, can be moved to MySQL, Microsoft Access,
and nearly any other portable data format that a researcher would need. Requests to gain read-only SQL access to the Curation
database can be made via the feedback link that appears at the bottom of any
MaizeGDB page. Data housed at MaizeGDB
are in the public domain and are freely available for use without a license.


### 2.3. Outreach

One of the strengths of MaizeGDB is its responsiveness to
community input, received either personally or by the feedback forms accessible
at the bottom of each page (Figure1(E)).
To provide outreach and user support as well as to solicit input from
researchers in a more active manner, several strategies are employed. The first is tutorials and basic information
on MaizeGDB. The MaizeGDB Tutorial
(Figure 1(F)) can be reached from the home page at the top of the left
margin. A new user can go through this
tutorial, and become familiar with how to use the site quickly. In addition, a “Site Tour” with an
overview with examples can be found under the “Useful pages” pull
down menu at the top of each page. More
specific tutorial examples and other educational materials are available via
the “Education” link, also within the “Useful pages” pull down menu. Also, on
many of the “Data Center” pages (available
from the left margin of the front page or via the “Useful pages” pull down) a
discussion of the topic of the page that is suitable for the general public
appears toward the bottom. Another form of outreach supported by MaizeGDB is assistance at meetings and conferences. Representatives from MaizeGDB attend and help
researchers at the Annual Maize Genetics Conference (usually in March), the
International Plant and Animal Genome Conference (January), and various other
meetings through direct interaction in person. Finally, researchers can request
a MaizeGDB site visit. About three times a year, an expert curator travels to various research locations and
provides tutorials and support for maize researchers. For these visits, the local maize researchers
are asked for a list of specific questions ahead of time. During the one to two day visits, researchers
interact in groups and one-on-one with the traveling curator to learn how to
utilize MaizeGDB for their research and to deposit data at MaizeGDB.


### 2.4. Community Support Services

MaizeGDB provides community support in several ways. Two members of the MaizeGDB team, MLS and
TES, serve as ex officio
members of the Maize Genetics Conference Steering Committee. They collect electronic abstracts for the
Annual Maize Genetics Conference and handle the preparation and printing of the
program for the conference. MaizeGDB personnel also manage regular community
surveys on behalf of the Maize Genetics Executive Committee. These surveys enable the Executive Committee
to summarize the overall research interest of the maize community and to advise
funding agencies on future research directions.
MaizeGDB personnel also manage the Executive Committee’s website (i.e.,http://www.maizegdb.org/mgec.php) and
conducts the Executive Committee’s elections. MaizeGDB houses the mailing list
for the annual Maize Newsletter and project personnel conduct semi-regular
mailings to the maize community on behalf of interested researchers by
maintaining an electronic list of researchers’ contact information. Potential mailings to this list are vetted by
the Executive Committee.


## 2.1. Kinds of Data in the Database that Link Genetic and Genome Sequence Information

MaizeGDB is the primary repository for the major genetic and
cytogenetic maps and includes details about genes, mutants, QTL (quantitative
trait loci), and molecular markers including 2500 RFLPs (restriction fragment
length polymorphisms), 4625 SSRs (simple sequence repeats), 363 SNP (single
nucleotide polymorphisms), 2500 indels (insertion/deletion sites), and 10 644 overgos (overlapping oligonucleotides). These data
are described using 1.27 millions synonyms, 42 000 primer sequences, 16 394 raw
scores from mapping based upon 16 panels of stocks, and 323 313 links to
GenBank [9] accessions. GenBank
accessions form the links between the genetic position on a chromosome, the
sequence records at MaizeGDB, and the EST (expressed sequence tag) and GSS
(genome survey sequence) contig assemblies at PlantGDB [10] and Dana Farber (The Gene Indices at http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=maize,
previously at TIGR [11]). All of the 3 520 247
sequences in MaizeGDB are accessible by BLAST [12] and can be filtered to report only mapped loci, including any
SSRs and overgos that may not be mapped genetically, but via BACs (bacterial
artificial chromosomes) in anchored contigs.The inclusion of the public
BAC FPC (Finger Print Contig) information [13] adds 439 449 BACs together with associated overgo, SSR, and RFLP
markers, which are used to assemble the contigs and to link contigs onto
genetic map coordinates. The order of
loci on the BAC contigs is represented by over 27 000 sequenced-based loci on
the IBM2 FPC057 maps (http://www.maizegdb.org/cgi-bin/displaymapresults.cgi?term=ibm2+fpc0507)
in MaizeGDB, by links to contigs at both the Arizona FPC site (http://www.genome.arizona.edu/) and the
genome sequencing project (http://www.maizesequence.org/). As the B73 genome sequence progresses, these
BAC sequences are added to MaizeGDB along with links to the sequencing project,
both from the BAC clones and from genetically mapped loci associated with a
BAC.The newest maps in MaizeGDB,
IBM SNP 2007 (http://www.maizegdb.org/cgi-bin/displaymapresults.cgi?term=ibm%20snp%202007),
are the first of a new generation of genetic maps from the Maize Diversity
Project (http://www.panzea.org/) kindly provided
pre-publication by Dr. Mike McMullen. The SNP loci on these maps are associated with allelic sequences from a
core set of maize and teosinte germplasm. Because the majority of the anticipated 1128 loci have been previously
mapped onto BAC clones [13, 14], these genetic maps tightly link sequence diversity to the B73
genome sequence.


## 2.2. Methods of Access, Environments, and the Database Back End

### 2.2.1. The Production Web Interface

Maize researchers primarily access MaizeGDB through the series of interconnected Web
pages available athttp://www.maizegdb.org/
(see Figure 1). These web pages are
dynamically generated and are written in PHP (the recursive abbreviation for
PHP Hypertext Preprocessor [15])
and Perl [16]. Through this interface, each page shows
detailed information on a specific biological entity (such as a gene) as well
as basic information about data associated with it (genes are associated with
maps, phenotypes, and citations, among others). These additional data types are linked to the gene page, enabling quick
access to alternative data views. The
site also includes links to related resources at other databases; genes, for
example, are linked to Gramene [7].Figure 1
The MaizeGDB home page. The most commonly utilized search
functionality for MaizeGDB is the search bar (A), which is available within the
header of any MaizeGDB page. To browse
data and to search specific data types using specific limiters, the Data
Centers (B) are also quite useful. Also
available is a Bin Viewer (C), which allows for a view of lots of data types
within the context of their chromosomal location. To enable access to the Data Centers
and other displays of interest from any MaizeGDB page, a pull-down menu for
“Useful pages” (D) is accessible on the header of any MaizeGDB page. The footer of all MaizeGDB pages contains a
context-sensitive “feedback form” link (E).
Researchers use the feedback form to report errors, ask questions, and
to contact the MaizeGDB team directly.
For newcomers to the site, the MaizeGDB Tutorial (F) can help them to
get a jump start on how to use the site.One may access these individual data pages by using either (1) the
search bar located at the top right of every page (Figure1(A)), or (2) data
type-specific advanced querying tools (accessible via the “Data Centers” links;
Figure 1(B)) on the left side of the home page, or (3) the Bin Viewer tool
(Figure 1(C)), which is located in the left margin of the home page or via a
pull down labeled “Useful pages” (Figure 1(D)) accessible at the top of any
MaizeGDB page. These tools allow researchers
to easily find relevant data displays.MaizeGDB's method of data
delivery has three primary goals: placing information within the framework of
its scientific meaning, making this information available to the researcher
with minimal input (often only the relevant term), and requiring minimal effort
from the researcher to comprehend the data displays. By focusing on biological context and ease of
use as the primary focus of this interface (the “production” Web interface),
the database is intended to be intuitive to the researcher as their click
stream follows a logical path of biological associations. Up-to-date site usage statistics can be
accessed online athttp://www.maizegdb.org/usage/.


### 2.2.2. Structure and Relationship of Environments: Production, Staging, and Test

The production Web interface, which most MaizeGDB users interact with, is only one component of the overall
MaizeGDB infrastructure (Figure2). The
data accessed by the production Web interface are typically updated on the
first Tuesday of each month. Prior to being in that Production Environment, the data are prepared for public
accessibility in a Staging Environment. In the Staging Environment, the most up-to-date information is
available, new data are added to the database, and existing data are updated
with new information. In addition to a
Web interface that appears identical to the one in the Production Environment,
the Staging Environment offers SQL (Structured Query Language) read-only access
to the community so that researchers interested in interacting with the data in
a more direct and customized manner can have access to the most up-to-date
information available. In addition, a Disaster Recovery system has been put
in place whereby the Curation Database is backed up in a compressed format to a
separate machine in Ames, Iowa daily.  Once weekly, the Ames file is copied to Columbia,
Missouri for off-site storage.Figure 2
Simplified infrastructure of MaizeGDB. The community of maize researchers can add
data to the database (downward-facing arrows from the uppermost yellow box) via
direct data deposition (upper left) and via a set of Community Curation Tools
that interacts with the Curation Database (upper center). Researchers are also allowed access to maize
data (upward-facing arrows from the lower dashed box) via a web interface that
can be accessed athttp://www.maizegdb.org/
(upper right) and by way of SQL access to the Curation Database, which houses
the most up-to-date data available (upper center). These functionalities are supported by two of
the three environments: Production and
Staging, respectively (upper dashed gold boxes). Available for use by MaizeGDB personnel to
facilitate data modeling and trial programming manipulations is a third
environment called Test (lower left dashed gold box), which is identical to the
Staging Environment. To ensure that the
most up-to-date copy of the database is backed up, a Disaster Recovery process
has been instituted (lower center dashed gold box) whereby a compressed copy of
the database is backed up to a separate machine in Ames, Iowa daily, and to a
server in Columbia, Missouri weekly.To aid in the modeling of new
types of data for inclusion in the MaizeGDB product and to enable programming
to be tried out in a safe place, a Test
Environment identical to the Staging Environment has been created. Note that three copies of the database
exist. While each environment and server
has a specific purpose, all are configured such that they could serve a backup
to each other. If any one server was to
fail, either of the other two could provide full, unrestricted data access and
site functionality. The curation
database is backed up on a daily basis and is available for download (http://goblin1.zool.iastate.edu/~oracle/)
for those who have Oracle Relational Database Management System (RDBMS)
installed locally.


### 2.2.3. Curation

Also available within the Staging Environment are Community
Curation Tools to enable researchers to add small datasets to the database
directly, as well as a set of Professional Curation Tools developed by Dr.
Marty Sachs’ group at the Maize Genetics Cooperation-Stock Center in Urbana-Champaign [17]. Whereas the Community
Curation Tools have many safeguards to help researchers enter data step-wise
and with enforced field requirements, the Professional Curation Tools allow
MaizeGDB project members as well as Stock Center personnel to enter datasets in
a more stream-lined and powerful fashion with fewer integrity enforcement rules
(which slow down the data entry process considerably). It also should be noted that data added to
the database via the Community Curation Tools are first marked as
“Experimental” that must be “Activated” by professional curators at
MaizeGDB. This ensures that only quality information is made publicly accessible.
The availability of a Curation Web interface (within the Staging
Environment) enables researchers to view the data as they will appear once they
are uploaded to Production. Few
researchers (about 30 at present) have Community Curation accounts. To increase the use of these tools, training
sessions are being organized (see Section 2.3, below). If researchers wish to deposit complex or
large datasets, it would not be reasonable to enter the data via the Community
Curation Tools because those tools work via a “bottom-up” approach whereby the
records are (1) built based upon the most basic information included in the
dataset and (2) entered one record at a time (i.e., not in bulk). For complex or large datasets, researchers
are encouraged to submit data files to the curators at MaizeGDB. Those data are added to the database directly
by curators and the database administrator.


### 2.2.4. Database Back End

Each environment’s server has
a perpetual license and is supported by Oracle RDBMS powered by2×2.0 GHz
Xeon processors, 4 GB of RAM, 5×73 GB Ultra 320 10 K RPM drives with Red Hat
Advanced Server 2.1 operating system installed. The curation database,
either partially or in its entirety, can be moved to MySQL, Microsoft Access,
and nearly any other portable data format that a researcher would need. Requests to gain read-only SQL access to the Curation
database can be made via the feedback link that appears at the bottom of any
MaizeGDB page. Data housed at MaizeGDB
are in the public domain and are freely available for use without a license.


## 2.2.1. The Production Web Interface

Maize researchers primarily access MaizeGDB through the series of interconnected Web
pages available athttp://www.maizegdb.org/
(see Figure 1). These web pages are
dynamically generated and are written in PHP (the recursive abbreviation for
PHP Hypertext Preprocessor [15])
and Perl [16]. Through this interface, each page shows
detailed information on a specific biological entity (such as a gene) as well
as basic information about data associated with it (genes are associated with
maps, phenotypes, and citations, among others). These additional data types are linked to the gene page, enabling quick
access to alternative data views. The
site also includes links to related resources at other databases; genes, for
example, are linked to Gramene [7].Figure 1
The MaizeGDB home page. The most commonly utilized search
functionality for MaizeGDB is the search bar (A), which is available within the
header of any MaizeGDB page. To browse
data and to search specific data types using specific limiters, the Data
Centers (B) are also quite useful. Also
available is a Bin Viewer (C), which allows for a view of lots of data types
within the context of their chromosomal location. To enable access to the Data Centers
and other displays of interest from any MaizeGDB page, a pull-down menu for
“Useful pages” (D) is accessible on the header of any MaizeGDB page. The footer of all MaizeGDB pages contains a
context-sensitive “feedback form” link (E).
Researchers use the feedback form to report errors, ask questions, and
to contact the MaizeGDB team directly.
For newcomers to the site, the MaizeGDB Tutorial (F) can help them to
get a jump start on how to use the site.One may access these individual data pages by using either (1) the
search bar located at the top right of every page (Figure1(A)), or (2) data
type-specific advanced querying tools (accessible via the “Data Centers” links;
Figure 1(B)) on the left side of the home page, or (3) the Bin Viewer tool
(Figure 1(C)), which is located in the left margin of the home page or via a
pull down labeled “Useful pages” (Figure 1(D)) accessible at the top of any
MaizeGDB page. These tools allow researchers
to easily find relevant data displays.MaizeGDB's method of data
delivery has three primary goals: placing information within the framework of
its scientific meaning, making this information available to the researcher
with minimal input (often only the relevant term), and requiring minimal effort
from the researcher to comprehend the data displays. By focusing on biological context and ease of
use as the primary focus of this interface (the “production” Web interface),
the database is intended to be intuitive to the researcher as their click
stream follows a logical path of biological associations. Up-to-date site usage statistics can be
accessed online athttp://www.maizegdb.org/usage/.


## 2.2.2. Structure and Relationship of Environments: Production, Staging, and Test

The production Web interface, which most MaizeGDB users interact with, is only one component of the overall
MaizeGDB infrastructure (Figure2). The
data accessed by the production Web interface are typically updated on the
first Tuesday of each month. Prior to being in that Production Environment, the data are prepared for public
accessibility in a Staging Environment. In the Staging Environment, the most up-to-date information is
available, new data are added to the database, and existing data are updated
with new information. In addition to a
Web interface that appears identical to the one in the Production Environment,
the Staging Environment offers SQL (Structured Query Language) read-only access
to the community so that researchers interested in interacting with the data in
a more direct and customized manner can have access to the most up-to-date
information available. In addition, a Disaster Recovery system has been put
in place whereby the Curation Database is backed up in a compressed format to a
separate machine in Ames, Iowa daily.  Once weekly, the Ames file is copied to Columbia,
Missouri for off-site storage.Figure 2
Simplified infrastructure of MaizeGDB. The community of maize researchers can add
data to the database (downward-facing arrows from the uppermost yellow box) via
direct data deposition (upper left) and via a set of Community Curation Tools
that interacts with the Curation Database (upper center). Researchers are also allowed access to maize
data (upward-facing arrows from the lower dashed box) via a web interface that
can be accessed athttp://www.maizegdb.org/
(upper right) and by way of SQL access to the Curation Database, which houses
the most up-to-date data available (upper center). These functionalities are supported by two of
the three environments: Production and
Staging, respectively (upper dashed gold boxes). Available for use by MaizeGDB personnel to
facilitate data modeling and trial programming manipulations is a third
environment called Test (lower left dashed gold box), which is identical to the
Staging Environment. To ensure that the
most up-to-date copy of the database is backed up, a Disaster Recovery process
has been instituted (lower center dashed gold box) whereby a compressed copy of
the database is backed up to a separate machine in Ames, Iowa daily, and to a
server in Columbia, Missouri weekly.To aid in the modeling of new
types of data for inclusion in the MaizeGDB product and to enable programming
to be tried out in a safe place, a Test
Environment identical to the Staging Environment has been created. Note that three copies of the database
exist. While each environment and server
has a specific purpose, all are configured such that they could serve a backup
to each other. If any one server was to
fail, either of the other two could provide full, unrestricted data access and
site functionality. The curation
database is backed up on a daily basis and is available for download (http://goblin1.zool.iastate.edu/~oracle/)
for those who have Oracle Relational Database Management System (RDBMS)
installed locally.


## 2.2.3. Curation

Also available within the Staging Environment are Community
Curation Tools to enable researchers to add small datasets to the database
directly, as well as a set of Professional Curation Tools developed by Dr.
Marty Sachs’ group at the Maize Genetics Cooperation-Stock Center in Urbana-Champaign [17]. Whereas the Community
Curation Tools have many safeguards to help researchers enter data step-wise
and with enforced field requirements, the Professional Curation Tools allow
MaizeGDB project members as well as Stock Center personnel to enter datasets in
a more stream-lined and powerful fashion with fewer integrity enforcement rules
(which slow down the data entry process considerably). It also should be noted that data added to
the database via the Community Curation Tools are first marked as
“Experimental” that must be “Activated” by professional curators at
MaizeGDB. This ensures that only quality information is made publicly accessible.
The availability of a Curation Web interface (within the Staging
Environment) enables researchers to view the data as they will appear once they
are uploaded to Production. Few
researchers (about 30 at present) have Community Curation accounts. To increase the use of these tools, training
sessions are being organized (see Section 2.3, below). If researchers wish to deposit complex or
large datasets, it would not be reasonable to enter the data via the Community
Curation Tools because those tools work via a “bottom-up” approach whereby the
records are (1) built based upon the most basic information included in the
dataset and (2) entered one record at a time (i.e., not in bulk). For complex or large datasets, researchers
are encouraged to submit data files to the curators at MaizeGDB. Those data are added to the database directly
by curators and the database administrator.


## 2.2.4. Database Back End

Each environment’s server has
a perpetual license and is supported by Oracle RDBMS powered by2×2.0 GHz
Xeon processors, 4 GB of RAM, 5×73 GB Ultra 320 10 K RPM drives with Red Hat
Advanced Server 2.1 operating system installed. The curation database,
either partially or in its entirety, can be moved to MySQL, Microsoft Access,
and nearly any other portable data format that a researcher would need. Requests to gain read-only SQL access to the Curation
database can be made via the feedback link that appears at the bottom of any
MaizeGDB page. Data housed at MaizeGDB
are in the public domain and are freely available for use without a license.


## 2.3. Outreach

One of the strengths of MaizeGDB is its responsiveness to
community input, received either personally or by the feedback forms accessible
at the bottom of each page (Figure1(E)).
To provide outreach and user support as well as to solicit input from
researchers in a more active manner, several strategies are employed. The first is tutorials and basic information
on MaizeGDB. The MaizeGDB Tutorial
(Figure 1(F)) can be reached from the home page at the top of the left
margin. A new user can go through this
tutorial, and become familiar with how to use the site quickly. In addition, a “Site Tour” with an
overview with examples can be found under the “Useful pages” pull
down menu at the top of each page. More
specific tutorial examples and other educational materials are available via
the “Education” link, also within the “Useful pages” pull down menu. Also, on
many of the “Data Center” pages (available
from the left margin of the front page or via the “Useful pages” pull down) a
discussion of the topic of the page that is suitable for the general public
appears toward the bottom. Another form of outreach supported by MaizeGDB is assistance at meetings and conferences. Representatives from MaizeGDB attend and help
researchers at the Annual Maize Genetics Conference (usually in March), the
International Plant and Animal Genome Conference (January), and various other
meetings through direct interaction in person. Finally, researchers can request
a MaizeGDB site visit. About three times a year, an expert curator travels to various research locations and
provides tutorials and support for maize researchers. For these visits, the local maize researchers
are asked for a list of specific questions ahead of time. During the one to two day visits, researchers
interact in groups and one-on-one with the traveling curator to learn how to
utilize MaizeGDB for their research and to deposit data at MaizeGDB.


## 2.4. Community Support Services

MaizeGDB provides community support in several ways. Two members of the MaizeGDB team, MLS and
TES, serve as ex officio
members of the Maize Genetics Conference Steering Committee. They collect electronic abstracts for the
Annual Maize Genetics Conference and handle the preparation and printing of the
program for the conference. MaizeGDB personnel also manage regular community
surveys on behalf of the Maize Genetics Executive Committee. These surveys enable the Executive Committee
to summarize the overall research interest of the maize community and to advise
funding agencies on future research directions.
MaizeGDB personnel also manage the Executive Committee’s website (i.e.,http://www.maizegdb.org/mgec.php) and
conducts the Executive Committee’s elections. MaizeGDB houses the mailing list
for the annual Maize Newsletter and project personnel conduct semi-regular
mailings to the maize community on behalf of interested researchers by
maintaining an electronic list of researchers’ contact information. Potential mailings to this list are vetted by
the Executive Committee.


## 3. Results and Discussion

To demonstrate how researchers utilize MaizeGDB, three example usage cases are
presented here. Because researchers with
very different goals can all utilize MaizeGDB to advance their work, the usage
cases are classified by research type: basic, translational, and applied. See Figure3 for examples of how these
research types fit together. By enabling
researchers to carry out workflows that support translational and applied
research, MaizeGDB plays a part in influencing crop development directly. Although a single researcher might even
include all of these three aspects in his/her research simultaneously, here the
researcher types are distinguished as follows: basic researchers investigate
the fundamental biology of the organism, translational researchers work to
determine the application of basic research outcomes for practical purposes [18], and applied researchers
implement proven technologies to improve crops.Figure 3
Three types of biological
research. Research can be divided into
three categories: basic, translational, and applied. Outcomes from basic research feed into
translational predictions, and developed uses for these findings constitute the
basis for developing real-world applications that benefit humanity and the
world. Listed after the flow of research
are definitions for each research type as well as medical and plant biological
models for how the different divisions are interrelated. Also shown are overviews of the example usage
cases presented in Section3.


### 3.1. Basic

Many basic researchers work with mutants to understand the
processes underlying biological phenomena.
Once a new mutant is found, there are several standard methods used to
elucidate normal gene functions. These
efforts include determining whether the mutant represents an allele of a
previously described gene, and if not, genetic mapping and cloning of the new
gene. Information stored in MaizeGDB is
useful in all of these steps.In a large screen for mutations that change pericarp pigmentation from red to some other color,
Researcher 1 has found a plant with a brownish-red pericarp coloration. She first wants search MaizeGDB to find all
known mutants that have red pericarp phenotypes to determine whether this
mutation represents a newly discovered gene.
Because she does not know how others might have described the phenotype,
she decides to browse existing phenotype terms and images. From the left margin of the MaizeGDB
homepage, she selects “Mutant Phenotypes” under “Data Centers-Functional.” On this page (http://www.maizegdb.org/phenotype.php),
she selects “pericarp color” from the pull down menu labeled
“Show only phenotypes relating to this trait” in the green search
bar. A number of possible mutant phenotypes
are returned, including “red pericarp.” Clicking on the “red pericarp” phenotype
link, she finds that the listed mutants are alleles of p1 (pericarp
color1). On this page (http://www.maizegdb.org/cgi-bin/displayphenorecord.cgi?id=13818),
she scrolls to the bottom and finds that there are many stocks that can be
ordered from the Maize Genetics Cooperation-Stock Center that carry P1-rr (an allele that causes red pericarp and red cob) or P1-rw (red pericarp and white cob). Having these stocks in hand will enable her
to test whether the new mutant represents an allele of the p1 gene, so she decides to order a few for complementation
analyses. Clicking on the stock links
listed on the variation/allele page allows her access to a shopping cart
utility (in the green right hand panel), and she orders seed from the Stock Center
directly through the MaizeGDB interface. She then goes back to the results of
her “pericarp color” query and repeats the process for “cherry pericarp,”
ordering stocks for r1-ch (colored1-cherry), also to be used in her
complementation analyses. (Another way
she could have found maize stocks that have red pericarp is the following: from the header of any page, select “Useful
pages” and click “Stocks.” This pulls up
the stock search page http://www.maizegdb.org/stock.php. In the green box, select stocks with the
phenotype “red pericarp” from the pull down menu of all phenotype names and
submit. A long list of stocks that
contain alleles of p1 with red
pericarp is returned. Alternatively, the Stock Center Catalog is
also available from the Stocks Data Center page.)Researcher 1 receives several
appropriate stocks and performs allelism tests and determines that her mutant
(which turns out to be recessive) is not allelic top1 or r1. She returns to MaizeGDB and again looks
through “Mutant Phenotype” results using the “pericarp color”
query. Listed there are brown pericarp,
orange pericarp, white pericarp, and lacquer red pericarp phenotypes in
addition to the red and cherry phenotypes she focused on initially. She finds that there is no stock available
for the brown pericarp phenotype (the brown
pericarp1 mutant has been lost), and all the others are alleles that confer
colored pericarp in the dominant condition as a result of the presence of P1 alleles. To determine whether the new mutation could
be an allele of bp1, she decides to
map it genetically.MaizeGDB houses the largest
collection of publicly available genetic maps of maize (currently over 1,337
maps). These include maps of genes
primarily defined by mutants with morphological phenotypes (“Genetic 2005”
is the most current), maps based on phenotypic molecular markers, and composite
maps where various maps have been integrated.
These maps can be easily accessed from the home page, via the left
margin link to “Data Centers-Genetic-Maps” (http://www.maizegdb.org/map.php). This page not only allows various map search
functions, but also provides information on the most popular maps and a handy
reference to explain more about the various composite maps.The maize genome
is divided into genetic bins of approximately 20 centiMorgans each and boundary
markers with nearby SSRs can be used for mapping (for further explanation seehttp://www.maizegdb.org/cgi-bin/bin_viewer.cgi). Researcher 1 decides to utilize SSRs to map
her gene to bin resolution. To find the
core markers from the home page, she clicks on “Tools-Bin Viewer” in the left margin of the
home page. This provides a list of the
core bin markers and a link to purchase relevant primers to screen her mapping
population. She generates a mapping
population, performs PCR experiments using the polymorphic markers, and maps
her mutant to bin 9.02.To see what genes
are located in bin 9.02, she goes back to the Bin Viewer (from the homepage),
and holds the curser over the image of chromosome 9 until she sees “bin
9.02,” then clicks. The result is a
long list of genes, other loci, sequences, EST contigs, SSRs, BACs, and other data
relating to bin 9.02. Searching through
this data, she sees thatbp1 is
listed under “other loci” in bin 9.02. This is a “lapsed locus” meaning
that the stock has been lost, but perhaps she has found a new allele!To see more
specific genetic mapping data onbp1,
she goes to the search bar along the top green bar of every page, selects
“loci” from the pull down menu, types “bp1” into the field
provided, and clicks the button marked “Go!”
This brings her to the bp1 locus page (http://www.maizegdb.org/cgi-bin/displaylocusrecord.cgi?id=61563)
where she can see that bp1 is placed
on three genetic maps. Clicking on each
map, Researcher 1 learns that in 1935, bp1 was mapped between sh1 and wx1 (shrunken1 and waxy1), two well-studied
genes. To search for molecular markers
suitable for fine structure mapping, she visits “Data Centers-Genetic-Maps” from the link on the home page. In the green Advanced Search box, she
enters sh1 and wx1 separately in the “Show only maps containing this
locus” lines. This returns only genetic maps that contain both genes.
She selects the map with the most markers—IBM2 2005 Neighbors 9 (with 2,488
markers). She finds sh1 at position 80.30, and wx1 at 185.00. To choose among several molecular
markers, Researcher 1 follows the available links leading her to information
about suitable primers, a number of variations (which can help to decide if
there may be a polymorphism in her mapping populations), gel patterns, and any
available GenBank accession numbers for sequences as well as sequenced
BACs. She finally selects markers and
performs fine structure mapping. As she
finds markers closer and closer to the gene, she can proceed with positional
cloning to determine whether the position is consistent with bp1 (nice examples of how this is done
can be found in [19–21]).


### 3.2. Translational

Research to understand the metabolic pathways that produce
pigmentation (like those outlined in Section3.1) are well studied in maize [22]. One example of a
well-characterized gene that confers pigmentation is p1, which encodes a transcription factor that regulates synthesis
of flavones such as anthocyanins [23]. The p1 gene, along with its adjacent duplicate pericarp color2 (p2),
controls pericarp and cob coloration and causes silks to brown when cut. One flavone produced by the pathway is
maysin, a compound which has been shown to be antinutritive to the corn ear
worm at concentrations above 0.2% fresh weight if husks limit access to the ear
such that feeding on silks is required for the insect to enter [24]. Many QTL for resistance
to corn earworm map near loci in the flavone synthesis pathway that are either
regulatory genes (such as p1 and p2), or at rate-limiting enzymatic
steps, such as c1 (chalcone synthase1) that contribute
maysin accumulation in silks [25]. Understanding how maysin
functions and how this information could be used for production agriculture is
Researcher 2’s area of expertise.Researcher 2 has investigated
maysin synthesis for some time, and has decided to clone an uncharacterized
maysin QTL nearumc105a, in the bin
9.02, which is bounded by bz1 and wx1 [24]. He believes that the QTL
may be a previously described, but lost, bp1 mutant thought to be involved in maysin synthesis. In the first step, he must first find
molecular markers to more finely map the region (his preference would be to use
SSRs, since members of the lab are already using them successfully). He plans to follow the strategy of chromosome
walking to narrow down the region of interest [19–21] followed by association mapping to identify the actual QTL
sequence [26, 27]. Knowing this sequence
would enable plant breeders to track the QTL for marker assisted selection.To find SSR data
for mapping to a bin region, Researcher 2 goes to the MaizeGDB home page and clicks
on “Data Centers-Genomic-Molecular Markers/Probes” in the left margin,
then clicks the “SSR” link at the top of the page (the link is located in“Specific
information is available on BACs, ESTs, overgos, and SSRs.”) Scrolling down to the green “Set Up Criteria”
box, he then selects bin 9.02 and submits a search request. A report is returned that lists the available
SSRs for bin 9.02, complete with primers, gel patterns for different germplasm,
and related maps. By going back to the
SSR page, he also downloads tabular reports of map locations of all SSRs on
chromosome 9, including those that have been anchored to a BAC contig. Using this information in the laboratory,
members of his research group perform mapping experiments using several SSRs in
bin 9.02 along with some others in the more distal part of bin 9.03. They discover that the mid-region peak for
the QTL is very near an SSR for bnlg1372,
which is anchored to a BAC contig.To find sequenced
BACs that may harbor the earworm resistance QTL, Researcher 2 uses the search
bar at the top of each MaizeGDB page to find the locusbnlg1372. At the top of the bnlg1372 page, he follows a link to the
contig 373 display at the Maize Sequencing Project site (http://www.maizesequence.org/). This is a rather large contig with many
sequenced BACs and assigned markers. At
the Maize Sequencing Project site, he uses the export function (a button at the
left margin) to view a text list of all the markers and sequenced BAC clones
that are available on the Finger Print Contig physical map. He finds that bnlg1372 is assigned to the region “19742100,1974700,” encompassed
by the sequenced BAC clone, c0324E10.
This information provides coordinates for viewing the region on a large
contig associated with bnlg1372, the
sequence of BAC c0324E10, and any other BACs nearby. Researcher 2 sequences
candidate regions in diverse germplasm and conducts association analysis using
silk maysin levels as a trait. This may
require other information about nearby markers, which also are accessible via
MaizeGDB [28, 29].Although these investigations
may require the development of further sequenced-based markers, Researcher 2
hopes that useful markers already exist and decides to explore MaizeGDB for any
other sequences or primer-based markers already assigned to the region of
interest including SNPs and indels. To
do this from the locus page forbnlg1372,
he clicks on the link to the most current IBM neighbors map listed, then
explores the “sequence” and “primer” view versions of the map by clicking on
the relevant links at the top of the page just under the map name. The primer view shows primers associated with
mapping probes along with the name of the probes—just what he needs to get going with the
association mapping work.


### 3.3. Applied

Interested in breeding plants for organic sweet corn production,
Researcher 3 has decided to use molecular markers to select for high maysin
content, which would increase resistance to the corn earworm—a cause of significant damage to sweet corn [30]. Although plants could be
genetically modified to carry the genes that confer high maysin levels in silks
(e.g., see [31]), Researcher 3’s farming clients require that their product be
certified as both organic and “GMO-free.”
To meet the producers’ needs, he has decided to pursue a marker-assisted
selection program to create high maysin sweet inbred lines, which he will use
to generate single-cross hybrids. To get
started with the work, he searches MaizeGDB to find references, markers, and
stocks for the project. Described here
are the details on how he could use MaizeGDB to (1) access stocks known to have
high maysin content directly and (2) locate relevant stocks based upon
associated data with no prior knowledge of which stocks he wants to find. An outline of how he uses MaizeGDB to
identify relevant selectable markers for tracking the various QTL associated
with maysin accumulation also is described.In the instance
of looking for particular stocks, Researcher 3 has identified GT114 as a high
maysin line from [25]. Using the green search
bar at the top of any MaizeGDB page, he searches “stocks” for “GT114.” At that page, he sees a brief annotation
stating that GT114 is a poor pollen producer and makes a note of that
observation and plans to cross by IA453 and IA5125, sweet lines that produce pollen
well, to ameliorate this potential difficulty.
Clicking the link to GT114, he sees that it is an inbred line derived
from GT-DDSA (DD Syn A) in Georgia, and it is made available via GRIN.
Selecting the link for GRIN, a page opens at that site (http://www.ars-grin.gov/cgi-bin/npgs/html/search.pl?PI+511314).
Listed there are the Crop Science Registration data, availability (noted as currently
unavailable, but a call to Mark Millard, maize curator at the maintenance site
indicates that he could access that stock in limited quantities if current
resources allow), and an image of bulk kernels among other information. The image of bulked kernels is especially
revealing: the kernels are yellow and the cob fragments appear red. Aware that
a red cob would be unacceptable for breeding sweet corn (the red pigment could
cause quite a mess for those cooking and eating corn on then cob), he decides
to search MaizeGDB for other available high maysin stocks.After a literature search of breeding stocks with a white cob that might still produce
maysin in the silks, Researcher 3 starts searching stocks for those known to
carry theP1-wwb allele, a dominant
allele of the p1 locus that confers
white pericarp, white cob, and browning silks.
By clicking the “Data Centers-Genetic-Stocks” link from the MaizeGDB homepage, he
arrives at the Stocks Data Center
page (which is also accessible via the “Useful pages” pull down at the top of
every MaizeGDB page). He uses the
Advanced Search box to limit the query by variation to those stocks associated
with the allele P1-wwb. A number of the stocks returned on the
results page have been evaluated for silk maysin accumulation (per associated
publications) and could be further investigated as potential breeding stocks.Although thep1 gene accounts for much of the
variability in maysin accumulation [32], association and QTL analyses for candidate genes for maysin
accumulation also have identified anthocyaninless1 (a1), colorless2 (c2), and white pollen1 (whp1) as contributing significantly [32, 33]. Researcher 3 can track
the dominant P1-wwb allele visually by selecting for browning silks given that the sweet
lines he will be using in the breeding program have silks that do not brown,
but tracking the other factors will require the use of molecular markers. To find molecular markers to select for
desirable alleles of, for example, a1,
Researcher 3 uses the search menu at the top of any page at MaizeGDB to find
“loci” using the query “a1.” The results
page (http://www.maizegdb.org/cgi-bin/displaylocusresults.cgi?term=a1) lists many loci with a1 as a substring, but shows the exact match
(the a1 locus) at the top of the
list. Clicking on that link shows the a1 locus page (http://www.maizegdb.org/cgi-bin/displaylocusrecord.cgi?id=12000),
which lists useful information including six probes/molecular markers that
could be used for tracking useful a1 alleles. Using the same process, he also
finds markers for the c2 and whp1 loci and sets to work determining
which markers to use for his selections.


## 3.1. Basic

Many basic researchers work with mutants to understand the
processes underlying biological phenomena.
Once a new mutant is found, there are several standard methods used to
elucidate normal gene functions. These
efforts include determining whether the mutant represents an allele of a
previously described gene, and if not, genetic mapping and cloning of the new
gene. Information stored in MaizeGDB is
useful in all of these steps.In a large screen for mutations that change pericarp pigmentation from red to some other color,
Researcher 1 has found a plant with a brownish-red pericarp coloration. She first wants search MaizeGDB to find all
known mutants that have red pericarp phenotypes to determine whether this
mutation represents a newly discovered gene.
Because she does not know how others might have described the phenotype,
she decides to browse existing phenotype terms and images. From the left margin of the MaizeGDB
homepage, she selects “Mutant Phenotypes” under “Data Centers-Functional.” On this page (http://www.maizegdb.org/phenotype.php),
she selects “pericarp color” from the pull down menu labeled
“Show only phenotypes relating to this trait” in the green search
bar. A number of possible mutant phenotypes
are returned, including “red pericarp.” Clicking on the “red pericarp” phenotype
link, she finds that the listed mutants are alleles of p1 (pericarp
color1). On this page (http://www.maizegdb.org/cgi-bin/displayphenorecord.cgi?id=13818),
she scrolls to the bottom and finds that there are many stocks that can be
ordered from the Maize Genetics Cooperation-Stock Center that carry P1-rr (an allele that causes red pericarp and red cob) or P1-rw (red pericarp and white cob). Having these stocks in hand will enable her
to test whether the new mutant represents an allele of the p1 gene, so she decides to order a few for complementation
analyses. Clicking on the stock links
listed on the variation/allele page allows her access to a shopping cart
utility (in the green right hand panel), and she orders seed from the Stock Center
directly through the MaizeGDB interface. She then goes back to the results of
her “pericarp color” query and repeats the process for “cherry pericarp,”
ordering stocks for r1-ch (colored1-cherry), also to be used in her
complementation analyses. (Another way
she could have found maize stocks that have red pericarp is the following: from the header of any page, select “Useful
pages” and click “Stocks.” This pulls up
the stock search page http://www.maizegdb.org/stock.php. In the green box, select stocks with the
phenotype “red pericarp” from the pull down menu of all phenotype names and
submit. A long list of stocks that
contain alleles of p1 with red
pericarp is returned. Alternatively, the Stock Center Catalog is
also available from the Stocks Data Center page.)Researcher 1 receives several
appropriate stocks and performs allelism tests and determines that her mutant
(which turns out to be recessive) is not allelic top1 or r1. She returns to MaizeGDB and again looks
through “Mutant Phenotype” results using the “pericarp color”
query. Listed there are brown pericarp,
orange pericarp, white pericarp, and lacquer red pericarp phenotypes in
addition to the red and cherry phenotypes she focused on initially. She finds that there is no stock available
for the brown pericarp phenotype (the brown
pericarp1 mutant has been lost), and all the others are alleles that confer
colored pericarp in the dominant condition as a result of the presence of P1 alleles. To determine whether the new mutation could
be an allele of bp1, she decides to
map it genetically.MaizeGDB houses the largest
collection of publicly available genetic maps of maize (currently over 1,337
maps). These include maps of genes
primarily defined by mutants with morphological phenotypes (“Genetic 2005”
is the most current), maps based on phenotypic molecular markers, and composite
maps where various maps have been integrated.
These maps can be easily accessed from the home page, via the left
margin link to “Data Centers-Genetic-Maps” (http://www.maizegdb.org/map.php). This page not only allows various map search
functions, but also provides information on the most popular maps and a handy
reference to explain more about the various composite maps.The maize genome
is divided into genetic bins of approximately 20 centiMorgans each and boundary
markers with nearby SSRs can be used for mapping (for further explanation seehttp://www.maizegdb.org/cgi-bin/bin_viewer.cgi). Researcher 1 decides to utilize SSRs to map
her gene to bin resolution. To find the
core markers from the home page, she clicks on “Tools-Bin Viewer” in the left margin of the
home page. This provides a list of the
core bin markers and a link to purchase relevant primers to screen her mapping
population. She generates a mapping
population, performs PCR experiments using the polymorphic markers, and maps
her mutant to bin 9.02.To see what genes
are located in bin 9.02, she goes back to the Bin Viewer (from the homepage),
and holds the curser over the image of chromosome 9 until she sees “bin
9.02,” then clicks. The result is a
long list of genes, other loci, sequences, EST contigs, SSRs, BACs, and other data
relating to bin 9.02. Searching through
this data, she sees thatbp1 is
listed under “other loci” in bin 9.02. This is a “lapsed locus” meaning
that the stock has been lost, but perhaps she has found a new allele!To see more
specific genetic mapping data onbp1,
she goes to the search bar along the top green bar of every page, selects
“loci” from the pull down menu, types “bp1” into the field
provided, and clicks the button marked “Go!”
This brings her to the bp1 locus page (http://www.maizegdb.org/cgi-bin/displaylocusrecord.cgi?id=61563)
where she can see that bp1 is placed
on three genetic maps. Clicking on each
map, Researcher 1 learns that in 1935, bp1 was mapped between sh1 and wx1 (shrunken1 and waxy1), two well-studied
genes. To search for molecular markers
suitable for fine structure mapping, she visits “Data Centers-Genetic-Maps” from the link on the home page. In the green Advanced Search box, she
enters sh1 and wx1 separately in the “Show only maps containing this
locus” lines. This returns only genetic maps that contain both genes.
She selects the map with the most markers—IBM2 2005 Neighbors 9 (with 2,488
markers). She finds sh1 at position 80.30, and wx1 at 185.00. To choose among several molecular
markers, Researcher 1 follows the available links leading her to information
about suitable primers, a number of variations (which can help to decide if
there may be a polymorphism in her mapping populations), gel patterns, and any
available GenBank accession numbers for sequences as well as sequenced
BACs. She finally selects markers and
performs fine structure mapping. As she
finds markers closer and closer to the gene, she can proceed with positional
cloning to determine whether the position is consistent with bp1 (nice examples of how this is done
can be found in [19–21]).


## 3.2. Translational

Research to understand the metabolic pathways that produce
pigmentation (like those outlined in Section3.1) are well studied in maize [22]. One example of a
well-characterized gene that confers pigmentation is p1, which encodes a transcription factor that regulates synthesis
of flavones such as anthocyanins [23]. The p1 gene, along with its adjacent duplicate pericarp color2 (p2),
controls pericarp and cob coloration and causes silks to brown when cut. One flavone produced by the pathway is
maysin, a compound which has been shown to be antinutritive to the corn ear
worm at concentrations above 0.2% fresh weight if husks limit access to the ear
such that feeding on silks is required for the insect to enter [24]. Many QTL for resistance
to corn earworm map near loci in the flavone synthesis pathway that are either
regulatory genes (such as p1 and p2), or at rate-limiting enzymatic
steps, such as c1 (chalcone synthase1) that contribute
maysin accumulation in silks [25]. Understanding how maysin
functions and how this information could be used for production agriculture is
Researcher 2’s area of expertise.Researcher 2 has investigated
maysin synthesis for some time, and has decided to clone an uncharacterized
maysin QTL nearumc105a, in the bin
9.02, which is bounded by bz1 and wx1 [24]. He believes that the QTL
may be a previously described, but lost, bp1 mutant thought to be involved in maysin synthesis. In the first step, he must first find
molecular markers to more finely map the region (his preference would be to use
SSRs, since members of the lab are already using them successfully). He plans to follow the strategy of chromosome
walking to narrow down the region of interest [19–21] followed by association mapping to identify the actual QTL
sequence [26, 27]. Knowing this sequence
would enable plant breeders to track the QTL for marker assisted selection.To find SSR data
for mapping to a bin region, Researcher 2 goes to the MaizeGDB home page and clicks
on “Data Centers-Genomic-Molecular Markers/Probes” in the left margin,
then clicks the “SSR” link at the top of the page (the link is located in“Specific
information is available on BACs, ESTs, overgos, and SSRs.”) Scrolling down to the green “Set Up Criteria”
box, he then selects bin 9.02 and submits a search request. A report is returned that lists the available
SSRs for bin 9.02, complete with primers, gel patterns for different germplasm,
and related maps. By going back to the
SSR page, he also downloads tabular reports of map locations of all SSRs on
chromosome 9, including those that have been anchored to a BAC contig. Using this information in the laboratory,
members of his research group perform mapping experiments using several SSRs in
bin 9.02 along with some others in the more distal part of bin 9.03. They discover that the mid-region peak for
the QTL is very near an SSR for bnlg1372,
which is anchored to a BAC contig.To find sequenced
BACs that may harbor the earworm resistance QTL, Researcher 2 uses the search
bar at the top of each MaizeGDB page to find the locusbnlg1372. At the top of the bnlg1372 page, he follows a link to the
contig 373 display at the Maize Sequencing Project site (http://www.maizesequence.org/). This is a rather large contig with many
sequenced BACs and assigned markers. At
the Maize Sequencing Project site, he uses the export function (a button at the
left margin) to view a text list of all the markers and sequenced BAC clones
that are available on the Finger Print Contig physical map. He finds that bnlg1372 is assigned to the region “19742100,1974700,” encompassed
by the sequenced BAC clone, c0324E10.
This information provides coordinates for viewing the region on a large
contig associated with bnlg1372, the
sequence of BAC c0324E10, and any other BACs nearby. Researcher 2 sequences
candidate regions in diverse germplasm and conducts association analysis using
silk maysin levels as a trait. This may
require other information about nearby markers, which also are accessible via
MaizeGDB [28, 29].Although these investigations
may require the development of further sequenced-based markers, Researcher 2
hopes that useful markers already exist and decides to explore MaizeGDB for any
other sequences or primer-based markers already assigned to the region of
interest including SNPs and indels. To
do this from the locus page forbnlg1372,
he clicks on the link to the most current IBM neighbors map listed, then
explores the “sequence” and “primer” view versions of the map by clicking on
the relevant links at the top of the page just under the map name. The primer view shows primers associated with
mapping probes along with the name of the probes—just what he needs to get going with the
association mapping work.


## 3.3. Applied

Interested in breeding plants for organic sweet corn production,
Researcher 3 has decided to use molecular markers to select for high maysin
content, which would increase resistance to the corn earworm—a cause of significant damage to sweet corn [30]. Although plants could be
genetically modified to carry the genes that confer high maysin levels in silks
(e.g., see [31]), Researcher 3’s farming clients require that their product be
certified as both organic and “GMO-free.”
To meet the producers’ needs, he has decided to pursue a marker-assisted
selection program to create high maysin sweet inbred lines, which he will use
to generate single-cross hybrids. To get
started with the work, he searches MaizeGDB to find references, markers, and
stocks for the project. Described here
are the details on how he could use MaizeGDB to (1) access stocks known to have
high maysin content directly and (2) locate relevant stocks based upon
associated data with no prior knowledge of which stocks he wants to find. An outline of how he uses MaizeGDB to
identify relevant selectable markers for tracking the various QTL associated
with maysin accumulation also is described.In the instance
of looking for particular stocks, Researcher 3 has identified GT114 as a high
maysin line from [25]. Using the green search
bar at the top of any MaizeGDB page, he searches “stocks” for “GT114.” At that page, he sees a brief annotation
stating that GT114 is a poor pollen producer and makes a note of that
observation and plans to cross by IA453 and IA5125, sweet lines that produce pollen
well, to ameliorate this potential difficulty.
Clicking the link to GT114, he sees that it is an inbred line derived
from GT-DDSA (DD Syn A) in Georgia, and it is made available via GRIN.
Selecting the link for GRIN, a page opens at that site (http://www.ars-grin.gov/cgi-bin/npgs/html/search.pl?PI+511314).
Listed there are the Crop Science Registration data, availability (noted as currently
unavailable, but a call to Mark Millard, maize curator at the maintenance site
indicates that he could access that stock in limited quantities if current
resources allow), and an image of bulk kernels among other information. The image of bulked kernels is especially
revealing: the kernels are yellow and the cob fragments appear red. Aware that
a red cob would be unacceptable for breeding sweet corn (the red pigment could
cause quite a mess for those cooking and eating corn on then cob), he decides
to search MaizeGDB for other available high maysin stocks.After a literature search of breeding stocks with a white cob that might still produce
maysin in the silks, Researcher 3 starts searching stocks for those known to
carry theP1-wwb allele, a dominant
allele of the p1 locus that confers
white pericarp, white cob, and browning silks.
By clicking the “Data Centers-Genetic-Stocks” link from the MaizeGDB homepage, he
arrives at the Stocks Data Center
page (which is also accessible via the “Useful pages” pull down at the top of
every MaizeGDB page). He uses the
Advanced Search box to limit the query by variation to those stocks associated
with the allele P1-wwb. A number of the stocks returned on the
results page have been evaluated for silk maysin accumulation (per associated
publications) and could be further investigated as potential breeding stocks.Although thep1 gene accounts for much of the
variability in maysin accumulation [32], association and QTL analyses for candidate genes for maysin
accumulation also have identified anthocyaninless1 (a1), colorless2 (c2), and white pollen1 (whp1) as contributing significantly [32, 33]. Researcher 3 can track
the dominant P1-wwb allele visually by selecting for browning silks given that the sweet
lines he will be using in the breeding program have silks that do not brown,
but tracking the other factors will require the use of molecular markers. To find molecular markers to select for
desirable alleles of, for example, a1,
Researcher 3 uses the search menu at the top of any page at MaizeGDB to find
“loci” using the query “a1.” The results
page (http://www.maizegdb.org/cgi-bin/displaylocusresults.cgi?term=a1) lists many loci with a1 as a substring, but shows the exact match
(the a1 locus) at the top of the
list. Clicking on that link shows the a1 locus page (http://www.maizegdb.org/cgi-bin/displaylocusrecord.cgi?id=12000),
which lists useful information including six probes/molecular markers that
could be used for tracking useful a1 alleles. Using the same process, he also
finds markers for the c2 and whp1 loci and sets to work determining
which markers to use for his selections.


## 4. Conclusions

Because MaizeGDB stores and makes accessible data of use for a
variety of applications, it is a resource of interest to maize researchers
spanning many disciplines. The fact that
basic research outcomes are tied to translational and applied data enables all
researcher types to utilize the MaizeGDB resource to further their research
goals, and connections to external resources like Gramene, NCBI, and GRIN make
it possible for researchers to find relevant resources quickly, irrespective of
storage location.At present, maize geneticists are at the cusp of a milestone: the
genome of the maize inbred B73 is being sequenced in the U.S., with
anticipated completion in 2008. In addition, scientists working in Mexico at Langebio (the National Genomics for
Biodiversity Laboratory) and Cinvestav (Centro de Investigacion y Estudios
Avanzados) have announced through a press release (July 12, 2007) that they
completely sequenced 95% of the genes with 4X coverage in a native Mexican
popcorn called palomero, though the data have not yet been released and the quality
of the data is unknown (seehttp://www.bloomberg.com/apps/news?pid=20601086&sid=aO.Xj8ybAExI&refer=latin_america). At present and as more maize sequence becomes
available relating sequences to the existing compendium of maize data is the primary need that must be met for maize
researchers in the immediate future.
Creating and conserving relationships among the data will enable
researchers to ask and answer questions about the structure and function of the
maize genome that previously could not be addressed. To address this need, MaizeGDB personnel will
create a “genome view” by adopting and customizing a Genome Browser that could
be used to integrate the outcomes of the Maize Genome Sequencing Project. For genome browser functionality, basic
researchers have an interest in visualizing genome structure, gene models,
functional data, and genetic variability.
Translational researchers would like to be able to assign values to
genomic and genetic variants (e.g., the value of a particular allele in a given
population) and to view those values within a genomic context. Applied researchers are interested in tagging
variants for use as selectable markers and retrieving tags for particular
regions of the genome. To best meet
these researchers’ needs, the “genome view” will allow researchers to visualize
a gene within its genomic context and a soon to be created “pathway view” will
enable the visualization of a gene product within the context of relevant
metabolic pathways annotated with Plant Ontology (http://www.plantontology.org/) [34] and Gene Ontology (http://www.geneontology.org/index.shtml)
[35] terms. By making sequence information
more easily accessible and fully integrated with other data stored at MaizeGDB,
it will become possible for researchers to begin to investigate how sequence
relates to the architecture of the maize chromosome complement. How are the chromosomes arranged? Is it possible to relate the genetic and
cytological maps to the assembled genome sequence? Are there sequences present at centromeres
that signal the cell to construct kinetochores, the machines that ensure proper
chromosome segregation to occur, at the correct site? MaizeGDB aims to enable researchers to
discover answers to such queries that will enhance the quality of basic maize
research and ultimately the value of maize as a crop. It will become possible to interrogate the
database to find answers to these and other complex questions, and the content
of the genome can better be related to its function, both within the cell and
to the plant as a whole. Convergence of traditional
biological investigation with the knowledge of genome content and organization
is currently lacking, and is a new area of research that will open up once a
complete genome sequence and a method for searching through the whole of the
data are both in place. It is the ability to investigate and answer
such basic research questions that will serve as the basis for devising sound
methods to breed better plants. Once the
relationships among sequence data and more traditional maize data like
genotypes, phenotypes, stocks, and so forth have been captured, it is important that
those data be presented to researchers in a way that can be easily understood
without requiring that they have any awareness of how the data are actually
stored within a database. It is these
needs—creating connections between sequence and
traditional genetic data, improving the interface to those data, and
determining how sequence data relate to the overall architecture of the maize
chromosome complement—that the MaizeGDB team seeks to fulfill in the
very near future.



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*Source: 496957-2008-08-20.xml*