Non-host resistance to wheat stem rust in Brachypodium species

Non-host resistance to wheat stem rust in Brachypodium species Dr. Melania Figueroa Assistant Professor Department of Plant Pathology and Stakman-Borlaug Center for Sustainable Plant Health University of Minnesota October, 2014

Outline Overall goal of our lab Introduction: Host vs. non-host resistance Plant immunity Experimental models in monocots and genetic sources of disease resistance against stem rust Brachypodium spp. Identification of genes conferring resistance to wheat stem rust in Brachypodium Reverse genetics approach Forward genetics approach Summary

Figueroa Lab our focus characteristics that enable a microbe to be a pathogen plantmicrobe interactions

Figueroa Lab our focus characteristics that enable a microbe to be a pathogen plant responses and traits that define host status plantmicrobe interactions

Figueroa Lab our focus characteristics that enable a microbe to be a pathogen plant responses and traits that define host status plantmicrobe interactions Engineering resistance to pathogens

Plant Immunity Non-host Host

Plant Immunity Non-host Host Resistance Susceptibility A continuum of layered defenses that results in a continuum of disease phenotypes

Plant Immunity Non-host Host Resistance Susceptibility Two major components Flor s Gene x Gene model

PAMP-triggered Immunity Effective in preventing infection by non-adapted pathogens MAMPs/PAMPs (Pathogen/Microbe-Associated Molecular Patterns) PRRs (Pattern Recognition Receptors) Pathogen Defense responses

Effector triggered Immunity Effective in preventing infection by adapted pathogens Pathogen Effectors NB-LRR type intracellular immune receptors Defense responses

Plant Immunity Non-host Host Resistance Susceptibility Resistance of all known genotypes of a plant species to all known races or isolates of a pathogen species It can act at the subspecies level, such as formae speciales (Puccinia graminis f.sp. tritici)

Plant Immunity Non-host Host Resistance Susceptibility Broad-spectrum resistance Potential to provide durable disease resistance Non-host resistance: one of the least understood phenomena Lack of genetically tractable systems

Non-host resistance models MAMPs/PAMPs Pathogen Effectors Evidence suggest that non-host and host resistance use similar metabolic or signaling pathways Non-host resistance models evoke a complex overlay of specific resistance and nonspecific defense responses

Experimental model plants to study monocots 40-54 Myrs 32-39 Myrs

Oryza sativa as model to study monocots ~ 420 Million bp 12 chr. (2n = 2x = 24) ~ 355 Million bp 5 chr. (2n = 2x = 10) Bread wheat ~ 17 Billion bp 7 chr. (2n = 6x = 42) Durum wheat ~ 12 Billion bp 7 chr. (2n = 4x = 28) Advantages: Small genome Genetically tractable Genetic and genomic resources available

Rice as model to study rust resistance Several cereal rust pathogens have been shown to infect and colonize the rice Puccinia graminis f. sp. tritici Ayliffe et al. 2011 Some rice cultivars support more pathogen growth than others. This variation was relatively subtle

Experimental model plant to study monocots Disadvantages: Rice is not a temperate grass, and is physically much larger and temperamental to grow Suboptimal phylogenetic positioning

Brachypodium distachyon as a model to study temperate cereals and grasses ~ 420 Million bp 12 chr. (2n = 2x = 24) ~ 355 Million bp 5 chr. (2n = 2x = 10) Bread wheat ~ 17 Billion bp 7 chr. (2n = 6x = 42) Durum wheat ~ 12 Billion bp 7 chr. (2n = 4x = 28)

Brachypodium distachyon as a model to study temperate cereals and grasses Small physical stature Self-fertility Short lifecycle Simple growth requirements Efficient transformation system

Orthology between Brachypodium and crop species The International Brachypodium Initiative, 2010 High genome colinearity and synteny occurring among species High probability of finding Brachypodium genes that are effective in wheat and barley

Development of Brachypodium as an experimental model plant Large germplasm collection and availability of recombinant inbred lines Extensive phenotypic variation in traits such as: plant height flowering time drought tolerance

Development of Brachypodium as an experimental model plant Large germplasm collection and availability of recombinant inbred lines Dr. Sean Gordon Extensive phenotypic variation in traits such as: plant height flowering time drought tolerance Evaluation of whole-genome sequence variation by deep sequencing indicates high genotypic variation Sequencing > 50 additional Brachypodium accessions Gordon et al. 2014

Development of Brachypodium as an experimental model plant Controversial phylogenetic status B. distachyon (2n = 10) Bidirectional crosses B. stacei (2n = 20) B. hybridum (2n = 4x = 30) Catalan et al. 2012 Garvin et al. 2008 Geographic distribution of Brachypodium spp.

Brachypodium displays non-host resistance to stem rust Non-host Host Resistance Susceptibility

Development of Brachypodium as an experimental model plant Figueroa et al. 2013 Brachypodium exhibits variation in stem rust resistance (from partially susceptible to almost immune)

Lesions per plant Stem rust infection in B. distachyon (Bd1-1) 70.0 60.0 50.0 40.0 30.0 20.0 10.0 Pathogens of Forage grasses Pathogen of wheat & barley 0.0 Pg-lo Pg-pp Pg-tr Bd1-1 displays different levels of resistance

Lesions per plant Stem rust infection in B. distachyon (Bd1-1) 70.0 Pathogens of Forage grasses Pathogen of wheat & barley Pg-lo Pg-pp Pg-tr 60.0 50.0 Bd1-1 40.0 30.0 20.0 10.0 Natural host 0.0 Pg-lo Pg-pp Pg-tr Figueroa et al. 2013 Bd1-1 acts as non-host for Pg-tr and pseudo-host for Pg-lo and Pg-pp

Differences in the ability to establish a biotrophic interaction Pg-lo Pg-pp Pg-tr 12 hpi 18 hpi 14% 13% 0.7% 68 hpi Figueroa et al. 2013

Differences in plant penetration % of plant penetration Pathogen of wheat & barley Pathogens of forage grasses hpi Substomatal vesicle

Differences in plant penetration % of plant penetration Pathogen of wheat & barley Pathogens of forage grasses hpi Pg-tr has attained the maximum percentage of plant penetration by 18 hpi The outcome of these interactions are determined at early stages of infection

A comparative RNA-seq analysis 3 biological replicates control Pg-tr Pg-pp Pg-lo 12 hpi 18 hpi Compare the plant transcriptional changes in response to Pg-tr vs Pg-pp and Pg-pp Determine changes in gene expression in comparison to mock inoculation (control)

A comparative RNA-seq analysis 3 biological replicates control 12 hpi Pg-tr Pg-pp Pg-lo 18 hpi RNA EXTRACTION CONSTRUCTION OF STRAND-SPECIFIC cdna LIBRARIES SEQUENCING Illumina HiSeq2000 Platform (101 bp SE) 27. 8 Multiplexing) ± 2.7 million reads per library

Putative perception mechanisms of stem rust MAMPs/PAMPs PRRs Pathogen Receptor-like proteins Effectors

Defense responses against stem rust Pg Cell wall reinforcement Accumulation of reactive oxygen species Production of secondary metabolites Pathogenesis-related proteins Activation of stress-related transcription factors

Functional validation of candidate genes Western Regional Research Center Brachypodium T-DNA Insertional Mutant Collection- Bragg et al. 2012 193 Genes of interest according to transcriptional data ~ 8,400 Selected mutants harbor T-DNA inserts in exons or introns in genes that displayed transcriptional up-regulation in response to stem rust infection

Functional validation of candidate genes Western Regional Research Center Brachypodium T-DNA Insertional Mutant Collection- Bragg et al. 2012 193 Genes of interest according to transcriptional data ~ 8,400 Dr. Claudia Castell- Miller Daniel Larson Selected mutants harbor T-DNA inserts in exons or introns in genes that displayed transcriptional up-regulation in response to stem rust infection Production of T2 seed from selected T-DNA insertion lines ( ~ 4.5 months)

Functional validation of candidate genes Screening for reduction or lack of stem rust resistance in B. distachyon Identification of homozygous lines by PCR Western Regional Research Center Brachypodium T-DNA Insertional Mutant Collection- Bragg et al. 2012 193 Genes of interest according to transcriptional data Christina Yoon Feng Li

Screening of Brachypodium accessions with several Pg-tr races, including Ug99 Jamie Kaufman BSL-3 Containment Facility MN Agricultural Experiment Station (MAES)/Minnesota Department of Agriculture (MDA)

Disease phenotypes after inoculation with Ug99 B. hybridum Bel1 Pob1 B. distachyon Tek-4 BdTR10H BdTR13H Mapping population ( F5 ) Foz-1 Mon-3 Mapping population (F2) Luc1 Adi-15 Koz-5

Disease phenotypes after inoculation with Ug99 Mapping loci linked to stem rust resistance

Hypothesis: ETI plays a role in the disease resistance outcomes MAMPs/PAMPs Pathogen PRRs Effectors Brachypodium-stem rust pathosystem

Summary Brachypodium spp. are a source of stem rust resistance that may be useful to improve crops such as wheat and barley. Our overall goal is to use B. distachyon derived-genes to generate of transgenic cereals as a strategy for crop protection. We hypothesize that both PTI and ETI contribute to the resistance to stem rust in Brachypodium spp. An experimental framework has been developed to identify genes in B. distachyon that may play a role in resistance to different stem rust isolates. Reverse and forward genetics approaches Functional validation of the role of candidate genes, especially those that may mediate pathogen recognition and antimicrobial activities is on-going.

Acknowledgements & Collaborators Members of the lab: C. Castell-Miller, The University of Minnesota, St. Paul, MN F. Li, The University of Minnesota, St. Paul, MN D. Larson, The University of Minnesota, St. Paul, MN C. Yoon, The University of Minnesota, St. Paul, MN L. van Lierop, The University of Minnesota, St. Paul, MN B. Pfender, USDA-ARS, Corvallis, OR, USA S. Seguin, USDA-ARS, Corvallis, OR, USA S. Alderman, USDA-ARS, Corvallis, OR, USA D. Garvin, USDA-ARS, St.Paul, MN USA J. Vogel, DOE Joint Genome Institute, Walnut Creek, CA S. Gordon, DOE Joint Genome Institute, Walnut Creek, CA R. Martin, USDA-ARS, Corvallis, OR, USA K. Cutter-Glover, USDA-ARS, Corvallis, OR, USA S. Filichkin, Oregon State University, Corvallis, Oregon T. Mockler, The Danforth Center, St. Louis, MI B. Steffenson, The University of Minnesota, St. Paul, MN M. Moscou, The Sainsbury Lab, Norwich, UK J. Bettgenhaeuse, The Sainsbury Lab, Norwich, UK M. Ayliffe, CSIRO, Canberra, Australia B. Wulff, John Innes Centre, Norwich, UK J. Kaufman, The University of Minnesota, St. Paul, MN L. Szabo, USDA-ARS, St. Paul, MN P. Dodds, CSIRO, Canberra, Australia Y. Jin, USDA-ARS, St. Paul, MN P. Olivera, The University of Minnesota, St. Paul, MN M. Newcomb, The University of Minnesota, St. Paul, MN M. Rouse, USDA-ARS, St. Paul, MN M. Martin, The University of Minnesota, St. Paul, MN J. Briggs, The University of Minnesota, St. Paul, MN Z. Mert, Central Research Institute for Field Crops, Ankara, Turkey J.Schilling, The University of Minnesota, St. Paul, MN J. Zhang, The University of Minnesota, St. Paul, MN J. Bradeen, The University of Minnesota, St. Paul, MN E. Tseng, Pacific Biosciences, Menlo Park, CA I. Grigoriev, DOE Joint Genome Institute, Walnut Creek, CA Z. Wang, DOE Joint Genome Institute, Walnut Creek, CA K. Hammel, US Forest Products Laboratory, Madison, WI C. Hunt, US Forest Products Laboratory, Madison, WI