Loss of premature stop codon in theWall-Associated Kinase 91(OsWAK91) gene confers sheath blight disease resistance in rice

Abstract

23The genetic arms race between pathogen and host plant is a tug of war that has been ongoing for 24 millennia. The "battles" are those of disruption, restoration of signaling and information 25 transmission on a subcellular level. One such battle occurs between rice an important crop that 26 feeds 50% of the world population and the sheath blight disease (SB) caused by the fungus 27 Rhizoctonia solani. It results in 10 30% global yield loss annually and can reach 50% under 28 severe outbreak. Many Receptor like kinases (RLKs) are recruited as soldiers in these battles. 29 Wall Associated Receptor Kinases (WAKs) a subfamily of receptor-like kinases have been 30 shown to play a role in fungal defense. Here we show that rice gene OsWAK91, present in the 31 major SB resistance QTL region on Chromosome 9 is a key component in defense against rice 32 sheath blight. An SNP mutation C/T separates susceptible variety, Cocodrie (CCDR) from the 33 resistant line MCR010277 (MCR). The resistant allele C results in the stop codon loss that 34 results in 68 amino acids longer C terminus carrying longer protein kinase domain and 35 phosphorylation sites. Our genotype and phenotype analysis of the top 20 individuals of the 36 double haploid SB population shows a strong correlation with the SNP. The susceptible allele 37 appears as a recent introduction found in the japonica subspecies reference genome and a 38 majority of the tropical and temperate japonica lines sequenced by the 3000 rice genome project. 39 Multiple US commercial varieties with japonica background carry the susceptible allele and are 40 known for SB susceptibility. This discovery opens the possibility of introducing resistance 41 alleles into high yielding commercial varieties to reduce yield losses incurred by the disease.42 43 103 point. Expression of known genes from each line, at each time point, was compared in a pairwise 104 fashion against the untreated, Day-0 sample for differential gene expression analysis. For CCDR 105 there were 105, 367 and 377 transcripts from 79, 281 and 320 genes at the Day-0 to Day-1, Day-106 0 to Day-3, and Day-0 to Day-5 comparisons, respectively. Whereas, in the MCR line, there 107 were 148 and 597 transcripts from 119 and 443 genes in the Day-0 to Day-3, and Day-0 to Day-5 108 comparisons, while there were no statistically significant differences in expression observed at 109 Day 0 to 1 (Figure-1B). In the Day-0 to Day-3 comparison, 17 common genes were up-regulated 110 in both the CCDR and MCR lines, and one common gene was down-regulated. Similarly, in the 111 6Day 0 to 5 comparison, 63 common genes in the CCDR and MCR lines were up-regulated, while 112 8 genes were down-regulated ( Figure 1B). In the susceptible CCDR line, there was a larger 113 number of differentially-expressed genes at Day-1, and increasing numberson and Day-3, unlike 114

Diverse Roles of MAX1 Homologues in Rice

“…Among that number, experimental data of the possible functions were available for 14 genes ( Table S10 ). The largest group of genes was involved in response to biotic stresses, including fungi ( Os01g0701700 , MR = 41.952 [ 167 ], Os04g0637000 , MR = 15.1, [ 168 ], Os01g0117200 , MR = 57.35, [ 169 ]; Os05g0409500 , MR = 64.312 [ 170 ]; Os03g0798200 , MR = 90.111, [ 171 ]), bacteria ( Os05g0365300 , MR = 89.778, [ 172 ], Os04g0637000 [ 173 ]) and insects ( Os04g0637000 [ 168 ]) ( Table S3 , Table S10 ). A wide range of abiotic stresses was represented in CGN of Os02g0221900 , including response to cold ( Os01g0701700 [ 127 ]; Os05g0409500 [ 128 ]), drought ( Os05g0557700 [ 174 ], Os05g0409500 , [ 57 ]), phosphorus status ( Os03g0348200 , MR = 50.279, [ 175 ]; Os04g0650700, MR = 20, [ 175 ]; Os05g0557700 [ 176 , 177 ]; Os03g0647600 , MR = 74.162 [ 178 ], Os01g0882800 , MR = 98.122 [ 64 ]), nitrogen status ( Os01g0870300 , MR = 90.427, [ 179 ]; Os01g0882800 [ 180 ]) and silicone ( Os05g0409500 , [ 157 ]) ( Table 3 , Table S10 ).…”

Understanding sheath blight resistance in rice: the road behind and the road ahead

“…Six different WAK proteins were up‐regulated in reaction to R. solani infection in resistant cultivar (Yuan et al , ). The full‐length protein product of OsWAK91 seemed to be related to ShB resistance (Al‐Bader et al , ). A recent proteomic study revealed that protein 14–3–3GF14f is highly stimulated in infected transgenic rice plants (Karmakar et al , ).…”

“…Silva et al () identified ten candidate genes within qShB9‐2 from resistant lines Jasmine 85, Teqing and MCR010277. Recently, four differentially expressed candidate genes between susceptible and resistant genotypes were detected from the vicinity of qShB9‐2 (Al‐Bader et al , ). Among the four, a C>T SNP in the OsWAK91 sequence has been shown to be associated with the resistant phenotype (Al‐Bader et al , ).…”

“…Recently, four differentially expressed candidate genes between susceptible and resistant genotypes were detected from the vicinity of qShB9‐2 (Al‐Bader et al , ). Among the four, a C>T SNP in the OsWAK91 sequence has been shown to be associated with the resistant phenotype (Al‐Bader et al , ). Interestingly, a recent study, dedicated to demarcating the physical region of qSB9‐TQ, has mapped it successfully to a 146‐Kb region flanked by the markers CY85 and Y86 (Figure ) (Zuo et al , ).…”

Identification of Cell Wall-Associated Kinases as Important Regulators Involved in Gossypium Hirsutum Resistance to Verticillium Dahliae

“…Some WAKs have been implicated in the response to pathogenic infection. Examples are Arabidopsis Wak1 [12], maize ZmWAK-RLK1 (Htn1) and ZmWAK (qHSR1) [21,22], wheat Stb6 and TaWAK6 [24,25], rice Xa4, OsWAK1 and OsWAK91 [16,17,26], and orange CsWAKL08 [27], which confer host plant disease resistance. Here, a total of 81 GhWAKs were systematically identi ed and analyzed for the rst time from a high-quality G. hirsutum genome (Table 1), which was assembled by integrating single-molecule real-time sequencing, BioNano optical mapping and high-throughput chromosome conformation capture techniques [23].…”