Genome re-sequencing analysis uncovers pathogenecity-related genes undergoing positive selection in Magnaporthe oryzae

Loss and Natural Variations of Blast Fungal Avirulence Genes Breakdown Rice Resistance Genes in the Sichuan Basin of China

Magnaporthe oryzae is the causative agent of rice blast, a devastating disease in rice worldwide. Based on the gene-for-gene paradigm, resistance (R) proteins can recognize their cognate avirulence (AVR) effectors to activate effector-triggered immunity. AVR genes have been demonstrated to evolve rapidly, leading to breakdown of the cognate resistance genes. Therefore, understanding the variation of AVR genes is essential to the deployment of resistant cultivars harboring the cognate R genes. In this study, we analyzed the nucleotide sequence polymorphisms of eight known AVR genes, namely, AVR-Pita1, AVR-Pii, AVR-Pia, AVR-Pik, AVR-Pizt, AVR-Pi9, AVR-Pib, and AVR-Pi54 in a total of 383 isolates from 13 prefectures in the Sichuan Basin. We detected the presence of AVR-Pik, AVR-Pi54, AVR-Pizt, AVR-Pi9, and AVR-Pib in the isolates of all the prefectures, but not AVR-Pita1, AVR-Pii, and AVR-Pia in at least seven prefectures, indicating loss of the three AVRs. We also detected insertions of Pot3, Mg-SINE, and indels in AVR-Pib, solo-LTR of Inago2 in AVR-Pizt, and gene duplications in AVR-Pik. Consistently, the isolates that did not harboring AVR-Pia were virulent to IRBLa-A, the monogenic line containing Pia, and the isolates with variants of AVR-Pib and AVR-Pizt were virulent to IRBLb-B and IRBLzt-t, the monogenic lines harboring Pib and Piz-t, respectively, indicating breakdown of resistance by the loss and variations of the avirulence genes. Therefore, the use of blast resistance genes should be alarmed by the loss and nature variations of avirulence genes in the blast fungal population in the Sichuan Basin.

Poaceae-specific cell wall-derived oligosaccharides activate plant immunity via OsCERK1 during Magnaporthe oryzae infection in rice

Many phytopathogens secrete cell wall degradation enzymes (CWDEs) to damage host cells and facilitate colonization. As the major components of the plant cell wall, cellulose and hemicellulose are the targets of CWDEs. Damaged plant cells often release damage-associated molecular patterns (DAMPs) to trigger plant immune responses. Here, we establish that the fungal pathogen Magnaporthe oryzae secretes the endoglucanases MoCel12A and MoCel12B during infection of rice (Oryza sativa). These endoglucanases target hemicellulose of the rice cell wall and release two specific oligosaccharides, namely the trisaccharide 31-β-D-Cellobiosyl-glucose and the tetrasaccharide 31-β-D-Cellotriosyl-glucose. 31-β-D-Cellobiosyl-glucose and 31-β-D-Cellotriosyl-glucose bind the immune receptor OsCERK1 but not the chitin binding protein OsCEBiP. However, they induce the dimerization of OsCERK1 and OsCEBiP. In addition, these Poaceae cell wall-specific oligosaccharides trigger a burst of reactive oxygen species (ROS) that is largely compromised in oscerk1 and oscebip mutants. We conclude that 31-β-D-Cellobiosyl-glucose and 31-β-D-Cellotriosyl-glucose are specific DAMPs released from the hemicellulose of rice cell wall, which are perceived by an OsCERK1 and OsCEBiP immune complex during M. oryzae infection in rice.

Hybrid de novo genome-reassembly reveals new insights on pathways and pathogenicity determinants in rice blast pathogen Magnaporthe oryzae RMg_Dl

Blast disease incited by Magnaporthe oryzae is a major threat to sustain rice production in all rice growing nations. The pathogen is widely distributed in all rice paddies and displays rapid aerial transmissions, and seed-borne latent infection. In order to understand the genetic variability, host specificity, and molecular basis of the pathogenicity-associated traits, the whole genome of rice infecting Magnaporthe oryzae (Strain RMg_Dl) was sequenced using the Illumina and PacBio (RSII compatible) platforms. The high-throughput hybrid assembly of short and long reads resulted in a total of 375 scaffolds with a genome size of 42.43 Mb. Furthermore, comparative genome analysis revealed 99% average nucleotide identity (ANI) with other oryzae genomes and 83% against M. grisea, and 73% against M. poe genomes. The gene calling identified 10,553 genes with 10,539 protein-coding sequences. Among the detected transposable elements, the LTR/Gypsy and Type LINE showed high occurrence. The InterProScan of predicted protein sequences revealed that 97% protein family (PFAM), 98% superfamily, and 95% CDD were shared among RMg_Dl and reference 70-15 genome, respectively. Additionally, 550 CAZymes with high GH family content/distribution and cell wall degrading enzymes (CWDE) such endoglucanase, beta-glucosidase, and pectate lyase were also deciphered in RMg_Dl. The prevalence of virulence factors determination revealed that 51 different VFs were found in the genome. The biochemical pathway such as starch and sucrose metabolism, mTOR signaling, cAMP signaling, MAPK signaling pathways related genes were identified in the genome. The 49,065 SNPs, 3267 insertions and 3611 deletions were detected, and majority of these varinats were located on downstream and upstream region. Taken together, the generated information will be useful to develop a specific marker for diagnosis, pathogen surveillance and tracking, molecular taxonomy, and species delineation which ultimately leads to device improved management strategies for blast disease.

Poaceae-specific cell wall-derived oligosaccharides activate plant immunity via OsCERK1 during Magnaporthe oryzae infection in rice

Many phytopathogens secrete cell wall degradation enzymes (CWDEs) to damage host cells and facilitate colonization. As the major components of the plant cell wall, cellulose and hemicellulose are the targets of CWDEs. Damaged plant cells often release damage-associated molecular patterns (DAMPs) to trigger plant immune responses. Here, we establish that the fungal pathogen Magnaporthe oryzae secretes the endoglucanases MoCel12A and MoCel12B during infection of rice (Oryza sativa). These endoglucanases target hemicellulose of the rice cell wall and release two specific oligosaccharides, namely the trisaccharide 3¹-β-D-Cellobiosyl-glucose and the tetrasaccharide 3¹-β-D-Cellotriosyl-glucose. 3¹-β-D-Cellobiosyl-glucose and 3¹-β-D-Cellotriosyl-glucose bind the immune receptor OsCERK1 but not the chitin binding protein OsCEBiP. However, they induce the dimerization of OsCERK1 and OsCEBiP. In addition, these Poaceae cell wall-specific oligosaccharides trigger a burst of reactive oxygen species (ROS) that is largely compromised in oscerk1 and oscebip mutants. We conclude that 3¹-β-D-Cellobiosyl-glucose and 3¹-β-D-Cellotriosyl-glucose are specific DAMPs released from the hemicellulose of rice cell wall, which are perceived by an OsCERK1 and OsCEBiP immune complex during M. oryzae infection in rice.

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs). The genetic variants in XMET genes are critical to predicate inter-individual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.