Open access peer-reviewed chapter

A Toolbox for Managing Blast and Sheath Blight Diseases of Rice in the United States of America

Written By

Yulin Jia, Melissa H. Jia, Xueyan Wang and Haijun Zhao

Submitted: 30 October 2018 Reviewed: 17 May 2019 Published: 11 June 2019

DOI: 10.5772/intechopen.86901

From the Edited Volume

Protecting Rice Grains in the Post-Genomic Era

Edited by Yulin Jia

Chapter metrics overview

1,672 Chapter Downloads

View Full Metrics


Rice blast disease caused by the fungus Magnaporthe oryzae and rice sheath blight disease caused by the fungus Rhizoctonia solani are two major hurdles for stable rice production worldwide. Presently, fungicides are still needed to manage these two devastating fungal pathogens. After two decades of research efforts, a toolbox has been assembled with the following components: (1) insight into pathogen genomic identity and pathogen avirulence (AVR) genes that can be used to enhance plant breeding; (2) new mapping populations and germplasm and genetic stocks that can be used as starting materials to identify effective host resistance (R) genes; (3) user-friendly disease evaluation methods that can be used to accelerate the identification and utilization of R genes; (4) validated effective R genes that are readily available for improving genetic resistance; (5) host genetic markers that can be used to accelerate the development of new resistant germplasms/cultivars; and (6) an improved understanding of resistance mechanisms that can facilitate the engineering of resistance in commercial varieties. Appropriate employment of these tools in breeding and crop protection will reduce production costs and create an environmentally benign, sustainable rice production system.


  • resource
  • resistance gene
  • avirulence gene
  • interaction
  • innate immunity

1. Introduction

In the twentieth century, researchers around the globe focused on studying plant pathogens to develop effective pesticides and cultural practices. Since the late twentieth century, this focus has shifted to identifying resistant resources, effective resistance (R) genes, and deploying them in precision agricultural systems. Rice has been grown in the United States for over 300 years and is concentrated in the Southern US, including the states of Arkansas, Mississippi, Missouri, Louisiana, Texas, and California. Among them, Arkansas is located in south-central USA at ~35° N latitude, 92° W longitude and produces ~50% of the total rice production in the USA. The total annual acreage of rice in the USA is presently about 1.5 million hectares, producing about 2% of the total world rice production. Rice is being consumed domestically and/or utilized as by-products. Recently, more rice is being consumed domestically, but the majority of rice produced in the USA is exported. As a result, the USA is one of the top exporting countries in the international market. Rice production in the USA has evolved to a highly mechanized, flood intensive irrigated system with the use of airplanes, tractors, computers, lasers, fertilizers, and pesticides at its disposal. Yield per hectare is currently about 7.5 tons/hectare [1] and has been one of the top breeding priorities. Rice breeding programs in the USA are associated with private companies such as Rice Tech Inc., BASF, and major state university agriculture experiment stations, consisting of one or more rice breeders, pathologists, and other scientists. Additionally, the USDA Agriculture Research Service (ARS) has conducted research in Stuttgart, Arkansas, since 1931 [2]. Soon after the establishment of the USDA, ARS, Dale Bumpers National Rice Research Center (DB NRRC, 1998), the molecular plant pathology program has been performing translational research to tackle the major constraints of rice production.

1.1 Rice blast disease

One of the major constraints for rice production in the USA is rice blast. Blast disease of rice is caused by the filamentous fungus Magnaporthe oryzae(synonymous with Pyricularia oryzae) which belongs to the M. grisea species complex. The M. grisea species complex is known to infect a wide range of monocots causing numerous diseases. However, infection of M. oryzae is highly specific to its host—rice (Oryza sativa) [3]. The infection of a M. oryzae isolate to an alternative species was only demonstrated under greenhouse conditions [4]. M. oryzae is a polycyclic pathogen that can reproduce 3–5 generations during a single crop season depending on geographic regions [5]. M. oryzae can survive in debris and seeds from previous crop seasons, and the fungi carrying debris and seeds are the primary sources of inoculum for blast epidemics [6, 7, 8]. Infection of M. oryzae starts with asexual conidia. The conidia germinate within a few hours after attachment and penetrate the host cells. Visible symptoms on rice leaves can be seen as early as 5 days after initial contact. A single blast lesion can produce thousands of conidia within a week and these conidia can spread to another rice plant through air, dew/water, and physical contact. Each conidium is capable of causing the loss of a single rice panicle (Figure 1).

Figure 1.

Photographs showing symptoms of leaf and panicle blast and asexual spores of rice blast fungus. (A) Panicle damage caused by blast; (B) severe blast lesions on rice seedlings affecting rice seedling establishment; (C) blast lesions on a rice leaf after diseased leaf from a field was placed in a petri dish with a prewetted filter paper for 24 h; and (D) four asexual spores of the rice blast fungus [9]. The pictures were taken either with an iPhone, with a dissecting microscope, or with a Nikon eclipse microscope.

1.2 Sheath blight disease

The soil-borne, necrotrophic Rhizoctonia solani species have a wide range of host plant species. The anastomosis group AG1-IA of R. solani infects rice and causes sheath blight disease. R. solani is a monocyclic fungus. The life cycle of R. solani begins with mycelia growth from sclerotia soon after attachment onto rice seedlings/plants. The mycelia then move upward along the sheaths and leaves of rice plants, ultimately resulting in damages on the sheaths, leaves, and grains. The life cycle ends with the formation of overwintering structures, sclerotia on the sheaths, leaves, seeds, and in soils [10] (Figure 2).

Figure 2.

Photographs showing sheath blight disease on the sheaths, leaves, and grains (A and B) and young mycelia sheath blight fungus with 45 and 90° angles (C). Pictures were taken with an iPhone or with a Nikon eclipse microscope.

1.3 The epidemics, climate, and damages

In the Southern US, rice blast disease can be found annually and occasionally results in significant crop damages. However, sheath blight disease occurs more often than blast disease partially due to high-density cultivation. An extended dew period and light are known to stimulate sporulation of M. oryzae. Light rain is known to keep plant surfaces wet and create near 100% relative humidity, helping the attachment and penetration of the conidia of M. oryzae. High humid conditions also favor the growth, infection, and spread of R. solani to other leaves and other plants [10]. In California, there is no rain during the rice-growing season. As a result, significant yield loss due to blast has not been reported [11]. Sheath blight disease has not been reported in California either despite a phenotypically similar disease, the aggregate sheath spot of rice caused by Rhizoctonia oryzae-sativae [12], commonly occurring. Presently, substantial fungicides have been used to prevent crop losses of these fungal diseases in the USA.


2. Pathogen genomic identity and pathogen avirulence (AVR) genes

Knowledge of pathogen populations is important to identify effective R genes and develop long-lasting strategies to prevent crop loss due to diseases. DNA fingerprint based on MGR586, mitochondrial DNA Restriction Fragment Length Polymorphism (RFLP), mating type, vegetative compatibility, virulence, DNA sequencing, simple sequence repeat (SSR) markers, and avirulence (AVR) gene analyses have been interchangeably used to characterize M. oryzae populations [13, 14, 15, 16, 17, 18, 19, 20]. The genetic identity of blast populations evaluated by SSR is not significantly different among rice production areas in the Southern US. The identity, however, is significantly different over the past 6 decades [19], suggesting that the environmental dynamics overtime such as weather, deployed rice varieties, and soil fertility in these years may play important roles in shaping the genetic identity of blast fungi. The pathogenicity of blast races (isolates) has been routinely evaluated with the international rice differential system since 1960s [20]. The most commonly found blast races are IB1, IB17, IB49, and IC17 while IA1, IA37, IA65, IA69, IA113, IB21, IB25, IB37, IB41, IC1, IC9, IE1k, IG1, and IH1 are the least commonly found blast races in the Southern US, whereas in California, IG1 is the only predominant blast race [19]. Similar blast races to those in the Southern US were also found in the winter nursery for the Southern US rice breeders in Puerto Rico [21].

The fungi purified from sheath blight-like diseased samples were evaluated with DNA markers, anastomosis grouping, speed of in vitro growth, and infection assays with detached leaf and microchamber assays [22]. All sheath blight-causing agents in 102 rice samples were determined to be R. solani with a diagnostic DNA marker derived from a ribosomal DNA internal transcribed spacer. Anastomosis grouping tests were conducted in cooperation with Dr. Craig Rothrock’s lab (Department of Plant Pathology, University of Arkansas, Fayetteville, Arkansas, USA). A total of 13 testers, namely, (ID Al 1-4, AG-B1); (ID521, AG-9); (ID CI, AG-8); (ID1529, AG-7); (NTA3-1, AG-6); (ID ST6-1, AG-5); (ID AH-1, AG-4); (ID W14 L, AG-3); (ID RI-64, AG2-2); (ID F56 L, AG2-1); (ID M43, AG1-1C); (ID Cs-Ka, AG1-IA); and (ID SFBV-1, AG1-IB), from different hosts were used. All the 102 isolates were determined to be IG1-IA. Three groups—fast growing (such as RR0321-4, RR0319-8, RR0101-1); intermediate growing (such as RR0305, RR0316-1); and slow growing (such as RR0316-1, RR0140-1, RR0141-1)—were identified by measuring the growth of each isolate in a nutrient-supported petri dish. The speeds of growth were found to be closely correlated with the lengths of disease lesions in the detached leaves of two rice varieties, suggesting that the fast-growing isolates were more virulent than those of slow-growing isolates [22]. These characterized isolates have been used to identify genetic resistance and molecular studies ever since.


3. Mapping populations and improved rice germplasm and genetic stocks

3.1 Mapping populations

Rice germplasms with different R resources is a prerequisite for developing improved rice varieties with R genes providing overlapped resistance to various blast races (isolates). In the Southern US, tropical japonica rice varieties are mainly grown, whereas in the state of California, temperate japonica rice varieties are grown. Major resistant resources to M. oryzae in the Southern US are mainly from indica rice varieties such as Tetep, Te Qing, and Zhe733. Complete resistant resources to R. solani have not been identified; however, moderate resistance from rice germplasms such as Jasmine 85 has been identified. These resistant resources were used to develop mapping populations and adaptive germplasms through single seed descend and doubled haploid breeding strategies (Figure 3 and Table 1).

Figure 3.

Photograph showing a view of the rice research plots of USDA ARS DBNRRC and the University of Arkansas Rice Research Center, Stuttgart, Arkansas, USA, 2016. Most rice resources and mapping populations were advanced in similar field plots. The picture was taken with a drone in 2016.

Name of genetic sources Plant identification Key information Number Year of release Reference
C/M doubled haploid GSOR 200001–200325 Sheath blight resistance 325 2006 [23]
Early/Katy mapping population GSOR 100361–100600 Blast resistance 240 2007 [24]
K/Z mapping population GSOR100001–100355 Molecular map/blast resistance 355 2007 [25]
SB5 mapping population GSOR 101601–102,174 Blast and sheath blight resistance 574 2009 [26]
Katy//M202 backcrossing lines GSOR 102501–102544 Blast resistance 42 2012 [27]
Weedy red rice mapping population 1 GSOR 303101–303287 Blast 187 2015 [28]
Weedy red rice mapping population 2 GSOR 303301–303536 Blast and sheath blight resistance 236 2015 [28]
USDA core collection GSOR 310001–311795 Blast resistance 1795 2015 [29, 30, 31, 32, 33]

Table 1.

List of major genetic resources for blast and sheath blight resistance in the USA. Most of the rice germplasms are available at USDA-GSOR (

3.2 Improved rice germplasms and genetic stocks

Germplasms with improved resistance to both blast and sheath blight diseases are helpful for rice breeders to develop new rice cultivars [34]. Four rice germplasms, LJRIL103 (PI 660982), LJRIL158 (PI 660983), LJRIL186 (PI 660984), and LJRIL220 (PI 660985), with resistance to both blast and sheath blight diseases were identified. They were identified from 800 progenies of a cross between US-adapted rice germplasm Lemont with Jasmine 85 [26]. These germplasms contain suitable agronomic traits in addition to the aromatic nature of LJRIL103, LJRIL158, and LJRIL186. Disease resistance and aromatic genes were tagged with DNA makers to ensure their incorporations.

Loss-of-function mutants can help identify the functionality of the corresponding wild-type allele [35]. For example, lesion mimic mutants (LMMs) with a phenotype resembling hypersensitive cell death without pathogen attack are useful for studying the molecular basis of plant innate immunity. A rice LMM was identified from the rice cultivar Katy after treatment with fast neutrons [36]. The severe lesion mimic phenotype of LMM1 can be induced by blast pathogens and water-related stress, respectively (M.S. Jia and Y. Jia, unpublished data). LMM1 has an enhanced resistance to both blast and sheath blight disease [36]. Genetic analysis suggests that a single recessive gene is responsible for the lesion mimic phenotype in LMM1. Further characterization of the underlying gene in LMM1 will help elucidate the mechanisms of plant innate immunity and abiotic stress responses.

The abovementioned mapping populations, characterized rice germplasms and genetic stocks, are now being used to map and clone R genes to both rice blast and sheath blight disease and develop DNA markers for marker-assisted breeding [37].


4. User-friendly disease evaluation methods

In the Southern US, genetic resistance to M. oryzae was investigated by Drs. Atkins, Johnston, and Marchetti [20, 38, 39]. Analyses of disease reactions to M. oryzae have been performed under field conditions where complex biotic and abiotic factors impacting the inheritance of resistance were encountered resulting in inconsistencies of disease reactions. In 1999, Dr. Marchetti and his colleagues demonstrated that disease reactions under an upland blast nursery were reliable to identify R genes among breeding lines [40]. Under greenhouse conditions, the phenotypes of rice to M. oryzae are categorized as 0–5 where 0 represents complete immunity, 1 represents hypersensitive cell death showing tiny brown spots, 2 represents infected lesions without mycelia, and, for susceptible reactions, 3–5 exhibit different sizes of lesions with visible mycelia coincident with different levels of resistance [32]. Phenotypes evaluated under the upland rice blast nursery were verified with 200 individuals of a mapping population under greenhouse conditions at DBNRRC [41]. Since then, the greenhouse methods have been used to determine the inheritance and genetic mechanisms of blast resistance [32, 41, 42]. In 2015, several IRRI monogenic lines generously donated by IRRI were added to further identify blast R genes under greenhouse conditions [43].

The early evaluation of sheath blight relied on replicated field plot experiments with fungal mycelia grown in corn chips or rye (Figure 4).

Figure 4.

Photographic presentation of the massive production of the sheath blight inoculant for field evaluation. Step 1: mixing A (corn chips) and B (rye) in a 2:1 weight ratio, adding water, and autoclaving twice. Step 2: growing mycelia in petri dishes containing PDA media until the appearance of white sclerotia (C). Step 3: mixing mycelia from C with a mixture of A and B from step 1, and incubating in a sterilized plastic or metal container for 3–5 days until the appearance of white sclerotia (D and E). Step 4: air drying mycelia and sclerotia in brown bags at 24°C with a fan (F). Step 5: grinding mycelia with a grinder (G) before inoculating plants under field conditions.

Disease reactions were scored by visually rating the disease severity on the sheaths and leaves of whole plants. The results of the evaluations are useful for mapping R genes. As an alternative, greenhouse methods such as detached leaf, soft-drink bottles, and parafilm methods were developed to validate and verify the function of R genes (Figures 5 and 6). These greenhouse methods are being used routinely for initial R gene discovery because they use less time, labor, land, and fertilizer.

Figure 5.

Photographic presentation of two controlled sheath blight evaluation methods. (1) Detached leaf method: mycelia grown on PDA media (A), and PDA plugs removed from a were placed onto detached leaves (6–12 cm in length) (B) at 24°C for 3 days. Symptoms of detached leaves from rice varieties jasmine 85 and M202 after inoculations with three R solani isolates versus the control PDA without pathogens (C and D). (2) Soft-drink bottle method: PDA plugs from A were placed onto the bottom of sheaths (E) and covered with 2-L soft-drink bottles (F) for 3–5 days until stable symptoms appeared. Length of lesions was measured for both methods as the severity of disease reactions.

Figure 6.

Parafilm method for sheath blight disease evaluation: a PDA containing mycelia (A) in a petri dish containing mycelia after 3 days of culturing at 30°C was removed and covered with parafilm and wrapped onto the second youngest leaf for 3–5 days (B) until stable symptoms appeared. A rating scale based on visual length and area of symptoms was assigned as indicated, with 0 representing immunity and 9 representing extreme susceptibility (C).

Figure 7.

Graphic presentation of resistance spectra of blast R genes in the USA. The common races, name of R genes, and chromosomal locations are indicated.


5. Effective R genes

5.1 Effective major R genes

A total of 14 known major blast R genes have been used in the USA since 1960s. Table 2 lists their chromosomal locations, representing germplasms, DNA markers to monitor respective R genes, and the avirulent and virulent races of these selected rice germplasms (Table 2). Based on field observations, most blast R genes are dominant whereas a single haplotype of R gene is effective for resistance. Among them, six dominant blast R genes Pia, Piks, Pi66(t), Pikh, Pikm, and Pi43(t)/Pi1, and one recessive R gene pid were on chromosome 11. Comprehensively, one was found on chromosome 2, two on chromosome 6, one on chromosome 8, one on chromosome 9, and two dominants on chromosome 12. Three of the dominant R genes, Pi9, Pi42(t), and Pi43(t), provide resistance to all races, while Pita2/Ptr is effective to all races except IE1k.

Chr. Name of R gene Selected germplasm Marker Name of blast races Reference
Avirulence Virulence
2 Pi-b Saber, Te-Qing RM208, Pib dom IB1, IB45, IH1, IG1, IC17, IE1, IE1k IB49, IB54 [31]
6 Piz(t) Zenith RM527, AP4791, AP5659-1, AP5659-5 IH1, IG1, IC17, IE1k IA45, IB1, IB49, IB54, IB33 [32]
6 Pi9 IR9660-48-1-1-2 (GSOR310687) KS6/KS28 IA45, IB1, IB49, IB54, IB45, IH1, IG1, IC17, IE1, IE1k [33]
8 Pi42(t) Zhe733 RM72 IA45, IB1, IB49, IB54, IB45, IH1, IG1, IC17, IE1, IE1k [44]
9 Pii Dawn IH1 [39]
11 Pia Bluebonnet IB1 [39]
11 Pikh Lebonnet RM224 IB45, IB54, IH1, IG1 IB49 [45]
Piks M2354 E/P
IB54 IA45, IB49, IB33, IB45, IH1, IG1, IC17, IE1, IE1k [46]
11 Pi66(t) DGWG IB54 IB45, IC17, IG1, IH1 [47]
11 Pikm Tsuyuake Q/P
IB45, IB54, IH1, IG1 IC17 [46]
11 Pi43(t)/Pi1 Zhe733 RM1233 IA45, IB1, IB49, IB54, IB45, IH1, IG1, IC17, IE1, IE1k [44]
11 Pid Lebonnet IB1 IA45, IB49, IB54, IB45, IH1, IG1, IC17, IE1, IE1k [45]
12 Pita Katy YL100/YL102, YL155/YL87 IB49, IC17 IE1k [29, 48, 49, 50]
12 Ptr (Pita2) Katy HJ16–12 IA45,IB1, IB49, IB54, IB45, IH1, IG1, IC17, IE1 IE1k [51, 52]

Table 2.

DNA markers and resistance efficacies of deployed blast R genes in the USA since 1960 (Figure 7).

The genetic markers linked or derived from the cloned R genes were developed to predict resistance function and to monitor the existence of each of the R genes [31, 32, 33, 44, 45, 46, 47, 48, 49, 50, 51, 52]. Differential blast races were identified (Table 2) and have been used to validate their predicted resistance efficacies.

5.2 Effective minor R genes

Distinct phenotyping variation of rice after infection via M. oryzae in different rice germplasms and in the same germplasm at different growth stages under greenhouse [53] and field conditions are also referred as dilatory, partial, field, and adult resistance interchangeably [54]. A total of 11 blast R quantitative trait loci (QTLs) responsible for a phenotypic variation ranging from 5.17 to 26.53% were identified with different blast races under greenhouse conditions [55] (Table 3) and verified with different blast isolates/races [56]. Using the same method, four additional blast R QTLs were identified from different rice germplasms [57].

QTL Chr. Blast race Marker interval Nearest marker locus (physical location in MB) Phenotypic variation (%) Nearest major R genes
qBLAST 3 3 IB45 RM251–RM338 RM282 (12.4) 5.17
qBLAST8.1 8 IB49 RM6863–RM72 RM1148 (4.0) 6.69 Pi36
qBLAST8.2 8 IC17 RM310–RM72 RM72 (6.8) 7.22
qBLAST9.1 9 IB54 RM257–RM108 RM257 (17.7) 4.64
qBLAST9.2 9 IC17 RM257–RM107 RM108 (17.9) 7.62 NBS-LRR
qBLAST9.3 9 IC17 RM107–RM245 RM215 (21.2) 4.49
qBLAST11 11 IB45 RM206–RM224 RM224 (27.8) 26.53 Pikm/Pik
IB54 RM206–RM224 RM224 (27.8) 19.6
qBLAST12.1 12 IB1 RM6998–OSM89 OSM89 (7.9) 5.44 Pi-ta/Ptr
qBLAST12.2 IB49 RM247–RM277 OSM89 (7.9) 9.7
ID1 RM247–RM277 OSM89 (7.9) 10.18

Table 3.

List of minor resistance genes to rice blast disease with indicated nearby major R genes and NBS-LRR proteins [55, 56].

Chr. indicates chromosome, MB indicates megabase pair, NBS-LRR indicates the protein with nucleotide-binding sites—leucine-rich repeat domain is often encoded by the R gene.

Thus far, major sheath blight R genes have not been identified. However, the major sheath blight R QTL qShB9-2 responsible for 24.3–27.2% of phenotypical variation using microchamber and mist chamber assays, respectively, and other nine minor R QTLs to sheath blight were also identified [58, 59]. These sheath blight R QTLs were verified with replicated field plot experiments in multiple locations [60]. This demonstrated that there exist useful genetic factors that can be used for breeding. DNA markers linked to these R QTLs can not only be used to pyramid resistance into new rice varieties via marker-assisted breeding but can also be used to clone and characterize genes underlying these R QTLs.


6. Resistance effectiveness

M. oryzae is a hemi-biotrophic organism with an extended period of biotrophic invasion that forced the evolution of robust major blast R genes in host. The resistance mediated by major blast R genes follows the gene-for-gene model where the R genes in rice detect the corresponding AVR genes in M. oryzae in triggering resistance responses [61]. The existence of AVR-Pita1 in US blast populations suggest that AVR-Pita1 may play an important role in fitness and pathogenicity. Ironically, what is needed for pathogens to survive also makes the pathogen less virulent and fit. This never-ending booming-and-busting cycle of host-pathogen interactions presents a unique opportunity to develop durable resistance. In the Southern US, after the blast epidemics in 1980s, a blast-resistant rice variety Katy was released in 1990 [62]. Katy contains a cluster of major R genes at the Pi-ta locus from the landrace indica variety Tetep and Piks from tropic variety Newbonnet [41]. Further analysis of Katy revealed that there are three linked blast R genes, Pi-ta and Pi-ta2/Ptr genes near the centromere of rice chromosome 12. Pi-ta is a classical R gene with NBS-LRR [63] and Ptr, which is allelic to Pi-ta2, encodes a predicted protein with four armadillo repeats [52]. Ptr was shown to confer resistance to a wide range of blast races except for IE1k and help Pi-ta with unknown mechanisms [52]. To date, a handful of rice varieties with the Pita, Pita2/Ptr cluster in a linkage block including Katy, Drew, Madison, Kaybonnet, Cybonnet, Banks, Ahrent, Catahoula, and Templeton have been released in the Southern US since 1990 [64, 65, 66]. Amei and colleagues showed that the Pi-ta gene has been bred into cultivated species of rice for decades [67]. The counter resistance from the pathogen usually occurs after breeders release a new resistant rice variety [68]. One of the counter resistance strategies of M. oryzae is to alter the structural integrity and expression of the AVR genes. The blast races (isolates) with partial, complete deletions, point mutations altering amino acids, and transposon insertions at the AVR-Pita1 locus have been found in commercial rice fields in the Southern US since the release of Pi-ta [16, 17, 18]. The resistance mediated by the Pi-ta/Pi-ta2/Ptr gene cluster has been stable for over two decades. Consistently, most blast populations were found to carry AVR-Pita1 [16, 17, 18] that verified the durability of resistance mediated by Pi-ta/Pi-ta2/Ptr. The observed resistance durability could be due to the lack of deployment of rice cultivars with the Pi-ta/Pi-ta2/Ptr genes to force the loss of AVR-Pita1. This is consistent with the fact that limited Pi-ta/Pi-ta2/Ptr containing rice varieties have been grown due to moderate yield advantages compared to other rice varieties lacking the genes since their releases [69]. Alternatively, it is also fully possible that AVR-Pita1 is important for the survival of M. oryzae with unknown mechanisms.


7. Summary

In the USA, any rice cultivar with one or two major blast R genes will continue to be effective to prevent rice blast disease. On the other hand, a combination of major R QTLs, suitable plant architecture, and growth rate should be considered to prevent sheath blight disease. A defense gene expression and cell reaction study suggested that strong resistance responses mediated by Pi-ta could be initiated as early as 24 h after pathogen inoculation [70]. However, the molecular mechanisms underlying Pi-ta or Ptr-mediated disease resistance pathways [71], the interactions between major blast R genes and R QTL [74], the role of micro RNA/long noncoding RNA in rice disease resistance [72, 73, 74, 75], and the relation of resistance versus productivity are still largely unclear [69]. Therefore, a clear understanding of the abovementioned plant innate immunity systems will be required for engineering resistance via genome editing. The lack of robust major R genes to R. solani may be due to the saprophytic nature of R. solani where the pathogen feed on the dead tissue of rice plants. Comparative analysis of defense genes in different hosts of R. solani may help identify useful R genes [76]. The genome of R. solani is mosaic and the draft sequence of R. solani IG1-IA genome is readily available [77]. Moving forward, the completion of whole genome sequencing will be the next urgent step to identify clues to manage R. solani. In brief, continued identification and characterization of R genes will be essential to safeguard rice crops. Ultimately, fungicides will be significantly reduced to prevent rice blast and sheath blight diseases in the future.



The authors thank Michael Lin, Tracy Bianco, Heather Box, Alan Sites, and Laduska Sells of USDA ARS DBNRRC and Mary Jia of Arkansas Schools of Math, Sciences and the Arts; Dr. Guangjie Liu of University of Arkansas Rice Research and Extension Center for excellent technical assistance; and Tyler Franzen for a photo taken by a drone. Special thanks are also given to all other scientists and supporting staff members of DB NRRC, and UA RREC for their continued support and useful discussion and interactions with the Molecular Plant Pathology program. For critical reviews we thank Drs. Trevis Huggins and Yong-Bao Pan of USDA ARS and two anonymous reviewers. USDA is an equal opportunity provider and employer.


  1. 1. Web page Ricepedia North America. Available from: [Accessed: 07 December 2018]
  2. 2. Stuttgart City Guide 2018-2019. p. 698
  3. 3. Couch BC, Fudal I, Lebrun M-H, Tharreau D, Valent B, van Kim P, et al. Origins of host-specific populations of the blast pathogen Magnaporthe oryzae in crop domestication with subsequent expansion of pandemic clones on rice and weeds of rice. Genetics. 2005;170:613-630. DOI: 10.1534/genetics.105.041780
  4. 4. Jia Y, Gealy D, Lin MJ, Wu L, Black H. Carolina foxtail (Alopecurus carolinianus): Susceptibility and suitability as an alternative host to rice blast disease (Magnaporthe oryzae [formerly M. oryzae]). Plant Disease. 2008;92:504-507
  5. 5. Jia Y, Zhou E, Lee S, Bianco T. Co-evolutionary dynamics of rice blast resistance gene Pi-ta and Magnaporthe oryzae avirulence gene AVR-Pita1. Phytopathology. 2016;106:676-683
  6. 6. Long DH, Correll JC, Lee FN, Tebeest DO. Rice blast epidmics initiated by infected rice grain on the soil surface. Plant Disease. 200l;85(6):612-616
  7. 7. Ravelson H, Ramonta RI, Tharreau D, Sester M. Long-term survival of blast pathogen in infected rice residues as major source of primary inoculum in high altitude upland ecology. Plant Pathology. 2018;67:610-618
  8. 8. Jia Y. A user-friendly method to isolate and single spore the fungi Magnaporthe oryzae and Magnaporthe grisea obtained from diseased field samples. Plant Health Progress. 2009;10:1-4. DOI: 10.1094/PHP-2009-1215-01-BR
  9. 9. Jia Y, Gealy D. Weedy red rice has novel resistance resources to biotic stress. Crop Journal. 2018;6:443-450. DOI: 10.1016/j.cj.2018.07.001
  10. 10. Uppala S, Zhou XG. Rice sheath blight. The plant health instructor. 2018. DOI: 10.1094/PHI-I-2018-0403-01. Available from: [Accessed 14 December 2018]
  11. 11. Greer C. What a Year for Rice Blast. Farmprogress. 2010. Available from: [Accessed 10 June 2019]
  12. 12. Gunnell PS, Webster RK. Aggregate sheath spot of rice in California. Plant Disease. 1984;68:529-531
  13. 13. Correll JC, Boza EJ, Seyran E, Cartwright RD, Jia Y, Lee FN. Examination of the rice blast pathogen population diversity in Arkansas, USA-stable or unstable? In: Wang G-L, Valent B, editors. Advances in Genetics, Genomics and Control of Rice Blast Disease. New York: Springer Sci +Businesses Media B.V.; 2009. pp. 217-228
  14. 14. Correll JC, Harp TL, Guerber JC, Zeigler RS, Liu B, Cartwright RD, et al. Characterization of Pyricularia grisea in the United States using independent genetic and molecular markers. Phytopathology. 2000;90(12):1396-1404
  15. 15. Li J, Li L, Jia Y, Wang Q , Fukuta Y, Li C. Characterization of field isolates of Magnaporthe oryzae with mating type, DNA fingerprinting, and pathogenicity assays. Plant Disease. 2016;100:298-303
  16. 16. Zhou E, Jia Y, Singh P, Correll J, Lee FN. Instability of the Magnaporthe oryzae avirulence gene AVR-Pita alters virulence. Fungal Genetics and Biology. 2007;44:1024-1034
  17. 17. Dai Y, Jia Y, Correll J, Wang X, Wang Y. Diversification and evolution of the avirulence gene AVR-Pita1 in field isolates of Magnaporthe oryzae. Fungal Genetics and Biology. 2010;47:974-980
  18. 18. Xing J, Jia Y, Correll JC, Lee FN, Cartwright R, Cao M, et al. Analysis of genetic and molecular identity among field isolates of the rice blast fungus with an international differential system, rep-PCR, and DNA sequencing. Plant Disease. 2013;97:491-495
  19. 19. Wang X, Jia Y, Wamishe Y, Jia MH, Valent B. Dynamic changes in the rice blast population in the USA over six decades. Molecular Plant-Microbe Interactions. 2017;30:803-812. DOI: 10.1094/MPMI-04-17-0101-R
  20. 20. Atkins JG, Robert AL, Adair CR, Goto K, Kozaka T, Yanagida R, et al. An international set of rice varieties for differntiaing races of Piricularia oryzae. Phytopathology. 1967;57:297-301
  21. 21. Jia Y, McClung AM. First report of multiple races of the rice blast fungus Magnaporthe oryzae in Puerto Rico. Plant Disease. 2016;10(6):1242. DOI: 10.1094/PDIS-12-15-1391-PDN
  22. 22. Wamishe Y, Jia Y, Singh P, Cartwright RD. Identification of field isolates of Rhizoctonia solani to detect quantitative resistance in rice under greenhouse conditions. Frontiers of Agriculture in China. 2007;1:361-367
  23. 23. Chu QR, Linscombe SD, Rush MC, Groth DE, Oard J, Sha X, et al. Registration of a C/M doubled haploid mapping population of rice. Crop Science. 2006;46:1416
  24. 24. Jia Y, Moldenhauer KAK. Development of monogenic and digenic rice lines for blast resistance genes Pi-ta, Pi-kh/Pi-ks. Journal of Plant Registrations. 2010;4:163-166
  25. 25. Liu G, Bernhardt J, Jia MH, Wamishe Y, Jia Y. Molecular characterization of the recombinant inbred line population derived from a japonica-indica rice cross. Euphytica. 2008;159:73-82
  26. 26. Jia Y, Liu G, Jia MH, McClung AM. Registration of a rice gene mapping population of Lemont × jasmine 85 recombinant inbred lines. Journal of Plant Registrations. 2015;9:128-132
  27. 27. Jia Y, Berger G, McClung AM. Registration of 42 blast resistant medium grain rice genetic stocks with suitable agronomic, yield, milling yield, and grain characteristics. Journal of Plant Registrations. 2016;10:316-324
  28. 28. Liu Y, Qi X, Gealy DR, Olsen KM, Caicedo AL, Jia Y. QTLs analysis for resistance to blast disease in US weedy rice. Molecular Plant-Microbe Interactions. 2015;28:834-844. DOI: 10.1094/MPMI-12-14-0386-R
  29. 29. Wang X, Fjellstrom R, Jia Y, Yan WG, Jia MH, Scheffler BE, et al. Characterization of Pi-ta blast resistance gene in an international rice core collection. Plant Breeding. 2010;129:491-501
  30. 30. Liu Y, Jia Y, Gealy DR, Goad DM, Caicedo AL, Olsen KM. Marker development for rice blast resistance gene Pi66(t) and application in USDA rice mini-core collection. Crop Science. 2016;56:1-8. DOI: 10.2135/cropsci2015.07.0422
  31. 31. Roychowdhury M, Jia Y, Jia MH, Fjellstrom B, Cartwright R. Identification of the rice blast resistance gene Pi-b in the national small grains collection. Phytopathology. 2012;102:700-706
  32. 32. RoyChowdhury M, Jia Y, Jackson A, Jia MH, Fjellstrom R, Cartwright R. Analysis of rice blast resistance gene Pi-z using pathogenicity assays and DNA markers. Euphytica. 2012;184:35-47
  33. 33. Scheuermann K, Jia Y. Identification of a Pi9-containing rice germplasm with a newly developed robust marker. Phytopathology. 2016;100(2):298-303
  34. 34. Jia Y, Liu G, Correa-Victoria FJ, McClung AM, Oard JH, Bryant RJ, et al. Registration of four rice germplasm lines with improved resistance to sheath blight and blast diseases. Journal of Plant Registrations. 2012;6:95-100
  35. 35. Jia Y. Understanding the molecular mechanisms of rice blast resistance using rice Mmutants. In: Shu QY, editor. Induced Plant Mutations in the Genomics Era. Rome: Food and Agriculture Organization of the United Nations; 2009. pp. 375-378
  36. 36. Jia Y. Registration of lesion mimic mutant of Katy rice. Crop Science. 2005;45:1675
  37. 37. Jia Y. Marker assisted selection for the control of rice blast disease. Pesticide Outlook. 2003;14:150-152
  38. 38. Atkins JG, Johnston TH. Inheritance in rice of reaction to races 1 and 6 of Piricularia oryzae. Phytopathology. 1965;55:993-995
  39. 39. Marchetti MA. Race-specific and rate-reducing resistance to rice blast in US rice cultivars. In: Zeigler RS, Leong SA, Teng PS, editors. Rice Blast Disease. Wallingford, UK: CAB International; 1994. pp. 231-244
  40. 40. Lai XH, Marchetti MA, Petersen HD. Comparative slow-blasting in rice grown under upland and flooded blast nursery culture. Plant Disease. 1999;83:681-684
  41. 41. Jia Y, Lee F, McClung A. Determination of resistance spectra to US races of Magnaporthe oryzae causing blast in a recombinant inbred line population. Plant Disease. 2009;93:639-644
  42. 42. Jia Y, Valent B, Lee FN. Determination of host responses to Magnaporthe grisea on detached rice leaves using a spot inoculation method. Plant Disease. 2003;87:129-133
  43. 43. Wang J, Correll JC, Jia Y. Characterization of rice blast resistance genes in rice germplasm with monogenic lines and pathogenicity assays. Crop Protection. 2015;72:132-138
  44. 44. Lee S, Wamishe Y, Jia Y, Liu G. Identification of two major resistance genes against race IE-1k of Magnaporthe oryzae in the indica rice cultivar Zhe733. Molecular Breeding. 2009;24:127-134
  45. 45. Marchetti MA, Lai X, Bollich CN. Inheritance of resistance to Pyriculaira oryzae rice cultivars grown in the United States. Phytopathology. 1987;77:799-804
  46. 46. Costanzo S, Jia Y. Sequence variation at the rice blast resistance gene Pi-km locus: Implications for the development of allele specific markers. Plant Science. 2010;178:523-530
  47. 47. Liu Y, Qi X, Young ND, Olsen KM, Caicedo AL, Jia Y. Characterization of resistance genes to rice blast fungus Magnaporthe oryzae in a “green revolution” rice variety. Molecular Breeding. 2015;35:52. DOI: 10.1007/s11032-015-0256-y
  48. 48. Jia Y, Wang Z, Fjellstrom RG, Moldenhauer KAK, Azam MA, Correll J, et al. Rice Pi-ta gene confers resistance to the major pathotypes of the rice blast fungus in the US. Phytopathology. 2004;94:296-301
  49. 49. Jia Y, Wang Z, Singh P. Development of dominant rice blast Pi-ta resistance gene markers. Crop Science. 2002;42:2145-2149
  50. 50. Jia Y, Redus M, Wang Z, Rutger JN. Development of a SNLP marker from the Pi-ta blast resistance gene by tri-primer PCR. Euphytica. 2004;138:97-105
  51. 51. Jia Y, Martin R. Identification of a new locus, Ptr(t) required for rice blast resistance gene Pi-ta-mediated resistance. Molecular Plant-Microbe Interactions. 2008;21:396-403
  52. 52. Zhao H, Wang X, Jia Y, Minkenberg B, Wheatley M, Fan J, et al. The rice blast resistance gene Ptr encodes an atypical protein and confers broad spectrum disease resistance. Nature Communications. 2018;9:2039. DOI: 10.1038/s4147-018-04369-4
  53. 53. Chen X, Jia Y, Wu B. Evaluation of rice responses to blast fungus Magnaporthe oryzae at different growth stages. Plant Disease. 2018;103:132-136. DOI: 10.1094/PDIS-12-17-1873-+-RE
  54. 54. Marchetti MA. Dilatory blast resistance in rice lines exotic to the southern United States. Plant Disease. 1983;67:1362-1364
  55. 55. Jia Y, Liu G. Mapping quantitative trait loci for resistance to rice blast. Phytopathology. 2011;101:176-187
  56. 56. Xing J, Jia MH, Correll JC, Yuan L, Deng H, Jia Y. Confirming and identifying new loci for resistance to rice blast disease using field isolates of Magnaporthe oryzae in the U.S. Crop Science. 2015;55:1-8
  57. 57. Yang H, Jia MH, Jia Y, Xing J, Venu R, Bellizzi M, et al. Molecular mapping of four blast resistance genes using recombinant inbred lines of 93-11 and Nipponbare. Journal of Plant Biology. 2013l;56:91-97
  58. 58. Liu G, Jia Y, Correa-Victoria F, Prado GA, Yeater KM, McClung A, et al. Mapping quantitative trait loci responsible for resistance to sheath blight in rice. Phytopathology. 2009;99:1078-1084
  59. 59. Nelson J, Oard JH, Groth D, Utomo H, Jia Y, Liu G, et al. Sheath-blight resistance QTLs and in japonica rice germplasm. Euphytica. 2011;184:23-34
  60. 60. Liu G, Jia Y, McClung A, Oard JH, Lee FN, Correll JC. Confirming QTLs and finding additional loci responsible for resistance to rice sheath blight disease. Plant Disease. 2013;97:113-117
  61. 61. Jia Y, McAdams SA, Bryan GT, Hershey H, Valent B. Direct interaction of resistance gene and avirulence gene products confers rice blast resistance. European Molecular Biology Organization Journal. 2000;19:4004-4014
  62. 62. Moldenhauer KAK, Lee FN, Norman RJ, Helms RS, Well RH, Dilday RH, et al. Registration of ‘Katy’ rice. Crop Science. 1990;30:747-748
  63. 63. Bryan GT, Wu K-S, Farrall L, Jia Y, Hershey HP, McAdams S, et al. A single amino acid difference distinguishes resistant and susceptible alleles of the rice blast resistance gene Pi-ta. The Plant Cell. 2000;12:2033-2045
  64. 64. Wang X, Lee S, Wang J, Ma J, Bianco TA, Jia Y. In: Rice WY, Bao J, editors. Current Advances on Genetic Resistance to Rice Blast Disease. London, UK: IntechOpen Limited; 2014. pp. 195-217. DOI: 10.5772/56824. Available from:
  65. 65. Jia Y. Artificial introgression of a large chromosome fragment around the rice blast resistance gene Pi-ta in backcross progeny and several elite rice cultivars. Heredity. 2009;103:333-339
  66. 66. Jia Y, Jia MH, Wang X, Liu G. Indica and japonica crosses resulting in linkage block and recombination suppression on rice chromosome 12. PLoS ONE. 2012;7(10):e43066
  67. 67. Amei A, Lee S, Mysore KS, Jia Y. Statistical inference of selection and divergence of rice blast resistance gene Pi-ta. Genes, Genomes, Genetics. 2014;4:2425-2432
  68. 68. Dean R, Van Kan JAL, Pretorius ZA, Hammond-Kosack KE, Di Pietro A, Spanu PD, et al. The top 10 fungal pathogens in molecular plant pathology. Molecular Plant Pathology. 2012;13:414-430. DOI: 10.1111/j.1364-3703.2011.00783.x
  69. 69. Wang X, Jia MH, Ghai P, Lee FN, Jia Y. Genome-wide association of rice blast resistance and yield related components of rice. Molecular Plant-Microbe Interactions. 2015;28:1383-1392
  70. 70. Wang Z, Lin H, Valent B, Rutger JN, Jia Y. Cytological and molecular analyses of disease resistance to the rice blast fungus. Chinese Journal of Rice Science. 2007;21:335-340
  71. 71. Costanzo S, Jia Y. Alternatively spliced transcripts of Pi-ta blast resistance gene in Oryza sativa. Plant Science. 2009;177:468-478
  72. 72. Chen X, Jia Y, Jia MH, Pinson S, Wang X, Wu B-W. Functional interactions between major rice blast resistance genes, Pi-ta and Pi-b, and minor blast resistance QTL. Phytopathology. 2018;108:1095-1103. DOI: 10.1094/PHYTO-02-18-0032-R
  73. 73. Venu RC, Jia Y, Gowda M, Jia MH, Jantasuriyarat C, Stahlberg E, et al. RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection. Molecular Genetics and Genomics. 2007;278:421-431
  74. 74. Li W, Jia Y, Liu F, Wang F, Fan F, Wang J, et al. Genome-wide identification and characterization of long non-coding RNAs responsible to Dickeya zeae in rice. RSC Advances. 2018;8:34408-34417
  75. 75. Li W, Jia Y, Liu F, Wang F, Fan F, Wang J, et al. Integration analysis of small RNA and degradome sequencing reveals microRNAs responsive to Dickeya zeae in resistant rice. Molecular Science. 2019;20:222. DOI: 10.3390/ijms20010222
  76. 76. Rioux R, Manmathan H, Singh P, Reyes B, Jia Y, Tavantzis S. Comparative analysis of putative pathogenesis-related gene expression in two Rhizoctonia solani pathosystems. Current Genetics. 2011;57:391-408
  77. 77. Nadarajah K, Razali NM, Cheah BH, Sahruna NS, Ismail S, Tathode M, et al. Draft genome sequence of Rhizoctonia solani anastomosis group 1 subgroup 1A strain 1802/KB isolated from rice. Genome Announcements. 2017;5(43):e01188-e01117. DOI: 10.1128/genomeA.01188-17

Written By

Yulin Jia, Melissa H. Jia, Xueyan Wang and Haijun Zhao

Submitted: 30 October 2018 Reviewed: 17 May 2019 Published: 11 June 2019