Genomic polymorphism data in Arabidopsis thaliana

Introduction

As sequencing and genotyping costs continue to decrease, association mapping (also known as linkage disequilibrium mapping) is emerging as a powerful, general tool for identifying alleles and loci responsible for natural variation. Although its application to human disease has received most attention (especially the International HapMap Project), association mapping has tremendous potential in a wide range of organisms. Because it naturally occurs as inbred lines, A. thaliana is almost ideally suited for association mapping: once a set of lines has been genotyped, they can be phenotyped over and over, for the same or for different traits, by the entire community. A multi-group effort to realize this potential has been under way for some time:

• With funding from the NSF 2010 Program (DEB-0115062), the Bergelson, Kreitman, and Nordborg labs set out to sequence 1,500 short fragments in a panel of 96 lines using standard PCR-based dideoxy sequencing. The 1,214 annotated sequence alignments generated by the project to date are available for download. More information about this project can be found here.
• Based on the results of the project just described, the Ecker and Weigel labs selected a subset of 20 "maximally diverse" lines for whole-genome re-sequencing using Perlegen technology. The initial results have recently been published (Clark et al., 2007; Kim et al., 2007), and the data are available here.
  
• With continued support from the NSF 2010 Project (DEB-0519961), the Bergelson, Kreitman, and Nordborg labs have joined forces with the Borevitz lab (supported by NIH GM073822) to develop an Affymetrix genotyping chip using SNPs discovered by the Perlegen re-sequencing (Kim et al., 2007), and use it to genotype around 1,300 lines. More information about this project can be found here.
  
• Somewhat further into the future, an effort to completely sequence many (or perhaps even all) of the 1,300 genotyped lines is underway. The "1001 Genomes Project" is spearheaded by Joe Ecker and Detlef Weigel.

A project to help integrate all these polymorphism data has also just been funded by the NSF 2010 Project (DEB-0723935).  More information about this project will be found here.