MaizeGDB is a community-oriented, long-term, federally funded
informatics service to researchers focused on the crop plant and
model organism Zea mays.
MaizeGDB is a founding member of
AgBioData,
a consortuim of agriculture-related online resources which is
committed to making agriculture-related research data FAIR.
GCV: A web-app that visualizes genomic context data in a single, federated interface by using functional annotations as a unit of search and comparison.
All locus types (points, probes, QTL, etc) may be accessed from this center. The QTL at MaizeGDB are a subset of data
available to about year 2003; each QTL has an assigned bin (about 10-20 cM resolution), or a bin range and may also be
found on the bin viewer. Recently we have begun to integrate published trait values data for germplasm
with public genotype data. See also the Diversity Center.
Simple Locus/QTL Search:
This search form allows you to just enter a name or partial name to quickly
retrieve the desired loci or QTL. If no Locus matches are found, this
search will attempt to find QTL Experiment and Trait matches. The latter
searches can be queried separately below.
Search Results :
Advanced Locus Search
Set Up Search Criteria
Check the boxes next to the fields you want to search; if you
just want to find records that have any value for that
attribute, check the box and leave the criteria alone. You can
use % or * as a wildcard in the text fields.
Show only loci:
Search by sequence
Useful Locus Reports
Here are some useful reports that summarize elements of locus data in the
database.
Locus Overview By Chromosome These tables provide a summary
of data for the loci on each chromosome. 1
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QTL Research Tools
QTL Locus Summary:
You can evaluate, sort, and download all of the MaizeGDB QTL loci together in one place.
QTL Data Downloads:
We are collecting QTL data files for download.
Please contribute!
Simple QTL Experiment Search:
The form below allows you to search quickly through our QTL data for
particular QTL experiments.
Use the wildcards '%' or '*' to find matches that contain your search term.
'^' at the beginning of search term will find matches that start with that term.
'$' at the end of search term will find matches that end with that term.
The above example search lets you find all experiments conducted by
Bill Beavis. Other interesting searches include
Abler 1991 (shows the series of
six Abler QTL experiments from 1991) or
Veldboom (a pair of highly-cited
QTL experiments).
Simple Trait Search:
The form below allows you to search quickly through our trait
data for particular traits.
Use the wildcards '%' or '*' to find matches that contain your search term.
'^' at the beginning of search term will find matches that start with that term.
'$' at the end of search term will find matches that end with that term.
The above example search lets you find all traits related to kernel
weight. Anther interesting search is
abscisic acid.
QTL Experiment Browser
Set Up Criteria
Discussion of Locus Data
What is a Locus?
All living things are described on a basic level by long strands of DNA.
These strands of DNA are broken down into a handful of distinct
structures called chromosomes; you can imagine a chromosome being much
like a ball of yarn in that it's a tightly-wrapped strand of DNA. A
locus, then, is any particular piece of information that refers
to a specific location on a certain chromosome. A locus can refer to a
particular location that describes a certain aspect of an organism (a
gene), or perhaps just a distinct portion of the chromosome with some
unique features (a marker).
What value does studying locus data have?
Studying locus data allows us to generate a strong overall picture of how
an organism works. By studying the relative locations of elements on
chromosomes and analyzing the differences between the locations, we
generate a picture of the inter-relations between genes and other genetic
elements and how they work together.
What is the connection between corn and locus data?
The locus data stored here provides information relevant to the study of
maize (corn). For instance, we have records
(like this one for adh1)
that provide detailed information on exactly where a particular element
is located in respect to other elements on corn chromosomes; these known
sets of distances between loci are called maps. We also provide
information on probes, which are genetic tools that are used to
specifically locate and describe a particular locus. By combining all of
this data together, we can create a very valid picture of specific pieces
of maize and learn how to treat corn diseases, improve corn yields, and
make corn more nutritious.
What is a QTL?
A QTL (or quantitative trait locus) refers to a
particular region of DNA that is associated with a particular trait. This
association is made through statistical methods based on the counting and
measurement of easily-observed traits, such as the weight of 1000 kernels,
the height of the second leaf at a particular stage of development, and so
forth.
MaizeGDB contains data outlining experiments that have
statistically determined the approximate location of a set of QTLs at once,
comprising a map that describes the
distances between the loci numerically.
Want to see an example? The
experiment Schon 1994a was
performed to establish a statistical relationship between
1000-kernel weight,
plant height, and
kernel protein content. The
result of this experiment was a
map, which researchers can then use
to help understand the genetic basis for that data.
What value does storing and studying QTL data have?
The data produced from this experiment provides statistical evidence for
the relationship between traits. Geneticists can use this information to
help determine gene location and function.