Plant & Animal Genomes XIII Conference

January 15-19, 2005
Town & Country Convention Center
San Diego, CA

High-Throughput Mapping Pipeline Of EST Based Sequences On Lettuce Genome. Genetic Map Validation, Visualization And Web Presentation.

Alexander Kozik , Steve Edberg , Barnaly Pande , David Caldwell , David Lee , Travis Kleeburg , Fallon Chen , Richard Michelmore

  Department of Vegetable Crops University of California Davis Davis CA 95616

Efficient genetic mapping of large numbers of markers requires the
coordination of the efforts of several people each of whom are
responsible for different parts of the operation. We have developed a
pipeline to map new markers on high density genetic maps. Major goals
and features of this pipeline are: 1. Minimizing the number of steps
from experimental data generation to entry of data into database. 2.
Automatic error checking and error handling of spreadsheets that contain
marker descriptions and raw scores, prior to uploading into the
database. 3. Simplified and controlled data flow to and from database
for mapping procedures. This pipeline includes: 1. Python Contig Viewer
for semiautomatic search of EST candidates with putative polymorphisms
and automatic design oligonucleotide primers for selected sequences
relative to potential intron positions. 2. Scripts that provide
controlled dataflow from spreadsheets into our relational mySQL
database. 3. Web interface (Dendrogram Viewer) to manipulate data in
database and pre-select sets of markers for further mapping while
maintaining linkage group designations from earlier maps. 4.
Visualization tools (CheckMatrix) to perform quality control and
validate maps. 5. Web interface to display results of mapping
graphically. Our database (http://cgpdb.ucdavis.edu/) provides
functionality to compare several genetic maps simultaneously as well as
the raw data that were used to construct the genetic maps. These
scripts are publicly available.