Prospects of Understanding the Molecular Biology of Disease Resistance in Rice

Abstract

Rice is one of the important crops grown worldwide and is considered as an important crop for global food security. Rice is being affected by various fungal, bacterial and viral diseases resulting in huge yield losses every year. Deployment of resistance genes in various crops is one of the important methods of disease management. However, identification, cloning and characterization of disease resistance genes is a very tedious effort. To increase the life span of resistant cultivars, it is important to understand the molecular basis of plant host-pathogen interaction. With the advancement in rice genetics and genomics, several rice varieties resistant to fungal, bacterial and viral pathogens have been developed. However, resistance response of these varieties break down very frequently because of the emergence of more virulent races of the pathogen in nature. To increase the durability of resistance genes under field conditions, understanding the mechanismof resistance response and its molecular basis should be well understood. Some emerging concepts like interspecies transfer of pattern recognition receptors (PRRs) and transgenerational plant immunitycan be employed to develop sustainable broad spectrum resistant varieties of rice.

Keywords: biotic stress; breeding; disease resistance; marker assisted selection; rice; signaling pathways; transcription factor.

Figure 1

Schematic representation of rice defense signaling cascades. Following the pathogen perception bypattern recognition receptors(PRRs) and R proteins, the rice plant initiates the diverse set of signaling cascades at different levels (PAMP-triggered immunity (PTI), left side and ETI, right side) involving numerous signal molecules, viz. ROS, NO, MAPKs, CDPKs, phytohormones to trade-off the pathogen invasion. In case of PTI, the host cell recognizes the common molecular pattern associated with most of the pathogens using PRRs (OsLYP6, OsFLS2, OsCEBiP, OsCERK1, Xa21, Xa24) and initiates MAPK kinase cascades (OsMKK4–OsMAPK6) that actually activate host defense responses via various transcriptional regulatory factors (OsWRKYs, OsNACs, OsNPR1, OsTGAs, OsbZIPs). However, PTI is suppressed by pathogen effectors, where they are encountered by the resistance genes (NBS-LRRs) that lead signaling to activate defense responses through phytohormonal activities. The archetypical defense pathways, SA and JA/ET pathways, mainly antagonistic to each other, are responsible for resistance against biotrophs and necrotrophs, respectively. The defense response includes production of PR proteins (glucanases, chitinases, defensins), production of ROS and NO, change in ion fluxes (Ca²⁺), cell wall strengthening (callose and lignin deposition) to confine the pathogen dissemination and disease development. GA, CK and Auxin act as negative regulators of plant innate immunity. BR prompts or suppresses disease susceptibility based on pathogen lifestyle or colonization. Furthermore, abscisic acid (ABA), well-known in abiotic stress tolerance, plays an ambiguous role, i.e., is both a positive and negative regulator of rice disease resistance based on the type and stage of infection; however, it predominantly actsas a negative regulator. The abbreviations used in the figure above represent viz. SA-salicylic acid; JA-Jasmonic acid, MeJA-Methyl Jasmonate; GB-Gibberellins, BR-Brassinosteroid; ET-Ethylene, CK-Cytokinin; ABA-Abscisic Acid, OsNPR1-Non-expressor of PR1 (NH1, NPR1 homolog1); OsCOI1-Coronatine Insensitive1 (JA receptor); OsJAZ8-Jasmonate ZIM domain protein, HPL3-Hydroperoxide lyase; ACS2-Enzyme for ET biosynthesis (ACC Synthase); OsEDR1-Enhanced Disease resistance 1 (TR1-like kinase); SLR1-slender rice1 (DELLA protein); GID1-encodes GA receptor; BRI1-BR Insensitive 1 (RLK) BR receptor.

Figure 2

Chromosome-wise distribution of major resistance genes identified from rice. Numbers 1–12 represent the chromosome of rice. Percentage of resistance gene sharing on each chromosome is shown in green solid line, while blue and red bars represent number of resistance genes on each chromosome and chromosome size (Mb), respectively.

Figure 3

Distribution of major resistance genes according to theirphysical location on the respective chromosomes. Different disease resistance gene categories plotted on the chromosomes are indicated by five color codes. The plot was generated on the basis of the nearest linked molecular makers.

Figure 4

QTLs distribution on rice chromosomes. Separate color codes are given for each group of QTLs. The physical distribution of QTLs is derived by the nearest linked molecular markers on each chromosome. BK, BS, FS, RSV and RYMV represent Bacterial Streak, Brown Spot, False Smut, Ricestripe virus and Rice yellow mottle virus resistance QTLs, respectively.