|VISSER, BOTMA - University Of The Free State|
|SAKTHIKUMAR, SHARADHA - Broad Institute Of Mit/harvard|
|PARK, ROBERT - Plant Breeding Institute|
|CUOMO, CHRISTINA - Broad Institute Of Mit/harvard|
Submitted to: Indian Council of Agricultural Research (ICAR) Monograph
Publication Type: Abstract Only
Publication Acceptance Date: 8/19/2013
Publication Date: 9/15/2013
Citation: Szabo, L.J., Visser, B., Sakthikumar, S., Johnson, J.L., Park, R., Cuomo, C. 2013. Understanding the genetic landscape of Puccinia graminis f. sp. tritici, from a global to country perspective. Indian Council of Agricultural Research (ICAR) Monograph. p. 3.
Technical Abstract: With the recent sequencing of the wheat stem rust pathogen (Puccinia graminis f. sp. tritici, Pgt) genome, an array of molecular tools has now become available to characterize the genetic variation of Pgt and develop new diagnostic methods for identification and detection of the Ug99 race group. The Pgt Genotyping Project is currently comprised of collaborators on five continents and collections from 18 countries. Two different genotyping platforms are being used, genome-wide re-sequencing and a SNP chip. Analysis of approximately 150 Pgt isolates has defined at least 10 distinct clades. Several of the clades contain isolates from different continents supporting that global movement of Pgt has occurred. The Ug99 race group forms a distinct clade and shares a common lineage with isolates from Africa, Australia and Europe. In addition, this project has demonstrated that a single race phenotype often contains multiple genotypes. The South African Pgt population is divided into two clades. The first clade represents the historical Pgt ancestry whereas the second consists of four members of the Ug99 race group. TTKSF was the first Ug99 race to be detected in South Africa in 2000. It is proposed that TTKSF entered South Africa as an exotic introduction and subsequently established itself as the dominant race within the population. Annual stem rust surveys and race analyses done by the ARC-SGI monitor the distribution and migration of races within and between the major wheat growing areas. Collected isolates are identified using infection type data on standard wheat differentials. To improve race identification, SNP and SSR technology was used to classify isolates collected during the 2010, 2011 and 2012 surveys. Results indicated a strong correlation between traditional and DNA based identification methods. The addition of the DNA methods serves as an example of how wheat stem rust research with a global aim, i.e. the molecular characterization of the Ug99 race group, adds value to understanding and describing pathogen variability in South Africa.