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Data processing protocols

Submit QTL data to GrainGenes

The discovery and mapping of quantitative trait loci (QTL) is an important part and sometimes the main goal of many mapping projects. While the primary and standard way of reporting your QTLs is through a publication, depositing your QTLs in a web database has the same advantages we mentioned for genetic maps. Mainly, they are amenable to computer searches, comparisons and linking to other pieces of information.

GrainGenes ( is a web database that stores QTL data and is ready to accept records with lots of different and complex information items. There is a template to assist in the preparation of data. The WheatCAP project deposits its QTL data in GrainGenes using a simplified template (you can find an example file here). If you are not participating of the WheatCAP you can check with the Graingenes curators ( to see whether you can use this shorter template.

QTL data in detail

The template has three worksheets, QTLs, which contains the specific information for each QTL; Locations, where the different environments tested are briefly described and a code is assigned to each; Reference, which lists bibliographical, web or other publications describing the study.

The QTLs worksheet holds most of the information and needs a further breakdown of its component. It has 12 columns:

  1. QTL
  2. trait
  3. trait code
  4. Trait ontology
  5. LOD score
  6. significant environments
  7. flanking markers
  8. most significant marker
  9. % variation explained
  10. map
  11. peak position
  12. contributor parent

1. QTL: The naming of a QTL follows the recommendations of the Catalogue of GeneSymbols for Wheat, 2008. Section I.3 (p.14). Briefly, the first letter has to be a "Q" to indicate it is a QTL, then follows a trait code, a period, the laboratory designator, a hyphen ("-") and the chromosome name. If there is more than one QTL for the same trait on the same chromosome, you designate each of them with numbers after the chromosome name. Sometimes when one of the QTL is on the short arm and the other on the long one, it can be clearer to name them by chromosome arm than by adding occurrence numbers.

The authors of the Gene Catalogue have created trait codes and assigned them to many wheat genes. Look for the appropriate codes for your QTLs in the summary table 1 of the catalogue (pdf file) or install the 2008 version of MacGene to make searches easier. If no code suits your trait, you can create a new one and communicate your proposal to one of the authors of the catalogue.

Regarding laboratory designator codes, two of the authors of the Gene Catalogue curate a list of three- or four-letter codes that univocally designates every contributing lab, these are known as laboratory designators and the list is available here. You should contact the authors of this list if you need a new laboratory designator code. WheatCAP members have these designator codes.

Anatomy of a QTL name:


    • Q: A QTL loci
    • Mxh: proposed code for mMixogram peak height
    • ucw: laboratory designator for Dubcovsky lab at the University of California, Davis
    • 7A.2: this is the second occurrence of a QTL for Mxh on chromosome 7A

2, 3: Trait and trait code: the name of the trait and its code as explained in the previous section.

4. Trait ontology (TO): this is a description of the trait using a controlled vocabulary organized in hierarchies. That is, traits are assigned a standardized name, a numeric code and parent-children relationships are established between traits. For example a more general trait called "anatomy and morphology related trait" with code TO:0000017 has several children, one of them is "seed anatomy and morphology trait" (TO:0000184), which in turn has a more specific children trait "seed color" (TO:0000486). The use of ontologies facilitates computer searches and the analysis of relationships between traits. To look for the TO terms that fit your traits and learn more about different ontologies, visit the ontologies pages in Gramene (

5. LOD score (logarithm of odds score): depending on the method you used for QTL discovery you can show here an exact value or a threshold.

6. Significant environments: a list of the environments where the QTL resulted statiscally significant. The environments are named according to the codes defined in the Locations worksheet.

7, 8. Flanking markers and most significant marker. The first cell shows the molecular markers flanking the QTL separated by a hyphen. The most significant marker is the loci that approximately coincides with the peak of the QTL.

9. % variation explained. You can add a note explaining what method was used to calculate the relative amount of variance explained by each QTL for a given trait.

10 Map. The name of the genetic map submitted to GrainGenes and that will be associated to the QTLs described. You can add here the chromosome number too, as shown in the example file.

11. Peak position: Position in cM of the QTL peak.

12. Contributor parent: name of the parent that contributes the positive effect to the QTL.

Submit your QTL data

Once your map file is ready you can submit it to the GrainGenes curators ( If you are a WheatCAP collaborator, submit your QTL file or questions about its preparation to Marcelo Soria.