Resistance in rice cultivars to the rice blast fungus Magnaporthe oryzae is complex and is controlled by both major genes and quantitative trait loci (QTLs). We undertook a genome-wide association study (GWAS) using the rice diversity panel 1 (RDP1) that was genotyped using a high-density (700 000 single nucleotide polymorphisms) array and inoculated with five diverse M. oryzae isolates. We identified 97 loci associated with blast resistance (LABRs). Among them, 82 were new regions and 15 co-localized with known blast resistance loci. The top 72 LABRs explained up to 98% of the phenotypic variation. The candidate genes in the LABRs encode nucleotide-binding site leucine-rich repeat (NBS-LRR) resistance proteins, receptor-like protein kinases, transcription factors and defence-related proteins. Among them, LABR_64 was strongly associated with resistance to all five isolates. We analysed the function of candidate genes underlying LABR_64 using RNA interference (RNAi) technology and identified two new resistance alleles at the Pi5 locus. We demonstrate an efficient strategy for rapid allele discovery using the power of GWAS, coupled with RNAi technology, for the dissection of complex blast resistance in rice.
Background Effective management of rice blast, caused by the fungus Magnaporthe oryzae , requires an understanding of the genetic architecture of the resistance to the disease in rice. Rice resistance varies with M. oryzae strains, and many quantitative trait loci (QTLs) affecting rice blast resistance have been mapped using different strains of M. oryzae from different areas. However, little is known about the genetic architecture of rice resistance against the M. oryzae population in Hunan Province, which is a main rice production area in South China. Results In this study, we used three isolates from Hunan Province and the rice diversity panel 1 to perform a genome-wide association study (GWAS) of blast resistance in rice. A total of 56 QTLs were identified. One of the QTLs is localized with the resistance gene Pik locus which confers resistance to all three isolates. Genomic sequence analysis of the resistant cultivars led to the identification of a new Pik allele, which we named Pikx . Yeast two-hybrid and co-immunoprecipitation assays between AvrPiks and Pikx confirmed that Pikx is a new allele at the Pik locus. Conclusions Our GWAS has identified many new blast resistance QTLs. The identified new Pik allele Pikx will be useful for breeding cultivars with high resistance to blast in Hunan and other South China provinces. Further research on the relationship between AvrPiks and Pikx will provide new insights into the molecular mechanism of rice resistance to M. oryzae . Electronic supplementary material The online version of this article (10.1186/s12284-019-0309-7) contains supplementary material, which is available to authorized users.
Background: Plenty of evidence has suggested that autophagy plays a crucial role in the biological processes of cancers. This study aimed to screen autophagy-related genes (ARGs) and establish a novel a scoring system for colorectal cancer (CRC). Methods: Autophagy-related genes sequencing data and the corresponding clinical data of CRC in The Cancer Genome Atlas were used as training data set. The GSE39582 data set from the Gene Expression Omnibus was used as validation set. An autophagy-related signature was developed in training set using univariate Cox analysis followed by stepwise multivariate Cox analysis and assessed in the validation set. Then we analyzed the function and pathways of ARGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Finally, a prognostic nomogram combining the autophagy-related risk score and clinicopathological characteristics was developed according to multivariate Cox analysis. Results: After univariate and multivariate analysis, 3 ARGs were used to construct autophagy-related signature. The KEGG pathway analyses showed several significantly enriched oncological signatures, such as p53 signaling pathway, apoptosis, human cytomegalovirus infection, platinum drug resistance, necroptosis, and ErbB signaling pathway. Patients were divided into high- and low-risk groups, and patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both training set and validation set. Furthermore, the nomogram for predicting 3- and 5-year OS was established based on autophagy-based risk score and clinicopathologic factors. The area under the curve and calibration curves indicated that the nomogram showed well accuracy of prediction. Conclusions: Our proposed autophagy-based signature has important prognostic value and may provide a promising tool for the development of personalized therapy.
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