Plant & Animal Genomes XVI Conference

January 12-16, 2008
Town & Country Convention Center
San Diego, CA

MIQAS - Minimal Information For QTL And Association Studies

Jan Aerts¹ , Wilfrid Carre¹ , Dirk-Jan De Koning¹ , Zhiliang Hu² , Dave Burt¹ , Andy Law¹ , Jim Reecy²

¹  Bioinformatics Group, Roslin Institute, Roslin EH25 9PS, Scotland, United Kingdom

²  Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA

The search for quantitative trait loci (QTLs) and genome-wide association studies is one of the main tools to elucidate the genetic origin of heritable traits. Although these experiments have provided very valuable information by themselves, an important part of this type of research in the future lies in meta-analyses where the results from existing studies are combined. However, the current practice used by the scientific community is more focused on single manuscripts than on integration with other external data, making data mining nearly impossible. Issues include the different ways to describe the QTL region (either by flanking markers or by centiMorgan intervals), incomplete disclosure of map positions, and inconsistency in marker naming.
To address these issues, we propose a community-supported set of minimal requirements for reporting on QTL and association studies (MIQAS), similar to the MIAME standard for microarray experiments. These requirements cover the description of the trait, population, statistical analysis, map and the QTLs or associations. Following these requirements will permit computational integration of existing QTL data and fine-mapping e.g. by comparing the location of a QTL in one species with orthologous locations in another species.
We believe that the MIQAS set of requirements will be key to the future of data mining in QTL and association studies.
More information on the project can be found at http://miqas.sourceforge.net.