Plant & Animal Genomes XVI Conference

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

Genomic Architecture Of Disease Resistance In Lettuce

Leah K McHale , Maria Jose Truco , Alexander Kozik , Tadeusz Wroblewski , Dean O Lavelle , Oswaldo E Ochoa , Smitha Mathrakott , Richard W Michelmore

  The Genome Center, University of California, Davis CA 95616, USA

The Compositae Genome Project (CGP) has generated over 700K ESTs from 18 species (http://cgpdb.ucdavis.edu/). Disease resistance is being studied in detail, among other traits important in domestication and weediness. 720 candidate genes have been identified by mining the EST database for sequences with similarity to genes involved in disease resistance in other species and through PCR with degenerate oligonucleotide primers. These candidate genes were categorized as resistance gene candidates (RGCs), resistance signaling pathway genes, defense response genes, and susceptibility factors. In addition, putative orthologs were identified from ESTs in five Lactuca species and studied for signals of positive selection, a characteristic of some genes involved in host-pathogen interactions. From 9,500 putative ortholog groups, 715 were identified with signals of positive selection. Candidate genes have been mapped relative to 36 phenotypes for resistance to diverse pathogens, providing a global view of the architecture of disease resistance in lettuce for efficient breeding and functional studies. Candidate genes are distributed across the nine chromosomes of lettuce. RGCs map into clusters and are more often associated with resistance phenotypes than are other classes of sequences. The function of candidate genes cosegregating with resistance phenotypes is being analyzed using RNAi transgenics and mutants. Taking advantage of sequence similarities in clusters of NBS-LRR encoding RGCs which co-localize with multiple phenotypic loci, RNAi transgenics are being used to silence families of genes. These transgenics are being used as genetic tester stocks to determine which phenotypes in a cluster are encoded by related sequences in diverse populations.