Identification of a Maize Locus That Modulates the Hypersensitive Defense Response,Using Mutant-Assisted Gene Identification and Characterization

Potentially useful naturally occurring genetic variation is often difficult to identify as the effects of individual genes are subtle and difficult to observe. In this study, a novel genetic technique called Mutant-Assisted Gene Identification and Characterization is used to identify naturally occurring loci modulating the hypersensitive defense response (HR) in maize. Mutant-Assisted Gene Identification and Characterization facilitates the identification of naturally occurring alleles underlying phenotypic variation from diverse germplasm, using a mutant phenotype as a “reporter.” In this study the reporter phenotype was caused by a partially dominant autoactive disease resistance gene, Rp1-D21, which caused HR lesions to form spontaneously all over the plant. Here it is demonstrated that the Rp1-D21 phenotype is profoundly affected by genetic background. By crossing the Rp1-D21 gene into the IBM mapping population, it was possible to map and identify Hrml1 on chromosome 10, a locus responsible for modulating the HR phenotype conferred by Rp1-D21. Other loci with smaller effects were identified on chromosomes 1 and 9. These results demonstrate that Mutant-Assisted Gene Identification and Characterization is a viable approach for identifying naturally occurring useful genetic variation.POTENTIALLY useful naturally occurring genetic variation is often difficult to identify as the effects of individual genes are subtle and difficult to observe. Furthermore, so many different alleles are available that it is a major challenge just to sift through the enormous diversity available. To this end, we recently conceptualized a simple yet effective method to discover and characterize variation present naturally in plant germplasm (Johal et al. 2008). This method, Mutant-Assisted Gene Identification and Characterization, makes use of a mutant phenotype for a gene affecting the trait of interest as a reporter to discover and analyze relevant, interacting genes present naturally in diverse germplasm. Mutant-Assisted Gene Identification and Characterization involves crossing a mutant to diverse germplasm and then evaluating the mutant progeny for transgressive changes (both suppressed and severe) in the mutant phenotype(s). If the mutation is recessive, the population needs to be advanced to the F₂ generation to be able to detect and analyze such variation. However, for a dominant or partially dominant mutant, evaluations can be made immediately in the F₁ to discover lines that contain suppressors or enhancers of the trait (mutation) under study. Mutant F₁ progenies from such crosses can then be propagated further to identify, map, and clone genes/QTL that affect the trait positively or negatively. In the case of maize and other species for which genetically characterized mapping populations are available, modifying loci can be rapidly mapped by crossing a mutant line to each member of a mapping population and evaluating the resulting F₁ families. In this study we provide a proof-of-concept for the Mutant-Assisted Gene Identification and Characterization technique, using it to identify loci involved in the defense response of maize.Plants are constantly exposed to numerous potential pathogens with diverse modes of attack. Nevertheless, it is rather rare to see plants succumbing to disease. One key reason for this is the presence of a highly effective and inducible defense system, a major component of which is the hypersensitive response (HR). HR is usually associated with a specific recognition event and is activated after other nonspecific resistance mechanisms have been overcome or evaded (see Bent and Mackey 2007). Although it was initially coined to refer to the rapid collapse of cells at the site of infection, over the years the term HR has been used to refer to both cell death and the associated induction of a number of other defense responses, including the accumulation of phytoalexins and pathogenesis-related (PR) proteins at the site of infection, to name a few (Mur et al. 2007). Reactive oxygen species such as superoxide and H₂O₂ appear to be causally involved in cell death underlying the HR response (Jones and Dangl 2006).HR is under the control of a subset of disease-resistance genes, commonly referred to as R genes. These R genes specifically recognize matching avirulence (Avr) effectors from the pathogen. Many R genes encode products containing a nucleotide-binding site (NBS) domain in the middle of the protein and a leucine-rich repeat (LRR) domain at the C-terminal end (Bent and Mackey 2007). R proteins are involved both in the recognition of the pathogen and the subsequent induction of the HR response. How R proteins remain in a quiescent but “vigilant” state remains to be established. Certain mutations in R genes have been found that abolish their dependence on AVR proteins for activation. Such aberrant R genes mostly behave as dominant or partially dominant alleles and trigger the HR constitutively in the absence of the pathogen (Hu et al. 1996; Zhang et al. 2003; Dodds et al. 2006). Two consequences of such “autoactive” or “ectopically active” R genes are a massive induction of cell death and the consequential stunting of the organism (Dodds et al. 2006). Although autoactive R genes have been found to exist in many plant species, the first few examples came from the maize Rp1 locus, which confers race-specific resistance to common rust, caused by Puccinia sorghi (Hu et al. 1996). Such autoactive R genes can be used to investigate HR genetics and etiology in the absence of confounding effects from the pathogen and constitute an excellent candidate for analysis using Mutant-Assisted Gene Identification and Characterization.The details of the HR cell death reaction as well as the pathway(s) that link R gene activation with the HR remain unclear (Mur et al. 2007). Despite considerable research over the past decade, only a few components have been found thus far. Some of these, Ndr1, Eds1, Pad4, Rar1, and Sgt1, were identified in mutagenesis screens conducted to identify mutants that failed to undergo an HR reaction in response to infection by an avirulent pathogen (reviewed in Bent and Mackey 2007). A few others, RIN4, for example, were identified in yeast two-hybrid assays using an NBS–LRR protein as bait (Mackey et al. 2003). Recently, an Arabidopsis gain-of-function mutant that carries a point mutation in an R gene analog (a gene with the structure of an R gene but not known to be involved in resistance to any pathogen) was used to isolate a few more potential genes in the HR pathway in a second site suppressor approach following mutagenesis with ethane methyl sulfonate (EMS) (Palma et al. 2005; Zhang and Li 2005; Goritschnig et al. 2007). A problem with approaches based on intentional mutagenesis is that they fail to uncover genes that have either redundant or essential functions. One way to avoid this problem would be to seek naturally occurring allelic variants affecting HR. Such natural variation is pervasive in all species, being generated and selected for over millions of years of evolution.Although natural variation has served as a constant provider of the R genes in all plant species, natural variability has not been tapped as a tool for understanding other aspects of the disease-resistance response (Holub 2007). The Rp1-D21 gene is an autoactive allele from the maize Rp1 disease-resistance locus that initiates HR randomly all over the plant (Pryor 1993; Collins et al. 1999; Sun et al. 2001). Our objective for this study was to use the Rp1-D21 gene phenotype as a test case for the Mutant-Assisted Gene Identification and Characterization approach. We show here that enormous variation exists in the maize germplasm that is capable of affecting the HR response positively or negatively and we identify loci that modulate expression of the HR phenotype segregating in the well-known Intermated B73 × Mo17 (IBM) advanced intercross line (AIL) population (Coe et al. 2002; Lee et al. 2002). This constitutes the first demonstration of the utility of the Mutant-Assisted Gene Identification and Characterization approach—an approach that is likely to prove widely applicable.