Comprehensive Genomic Analysis of Bipolaris sorokiniana Strains: Insights Into Genetic Diversity and Pathogenicity

被引:0
作者
Shukla, Anand Kumar [1 ,2 ]
Sahoo, Rosaleen [1 ,2 ]
Kadoo, Narendra [1 ,2 ]
机构
[1] CSIR Natl Chem Lab, Biochem Sci Div, Pune, India
[2] Acad Sci & Innovat Res AcSIR, Ghaziabad, India
关键词
Cochliobolus sativus; comparative genomics; effector proteins; pathogen variability; secondary metabolites; spot blotch; SPOT BLOTCH RESISTANCE; PROTEIN; BARLEY; WHEAT; ANNOTATION; DISEASES;
D O I
10.1111/ppa.70008
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Bipolaris sorokiniana is an important plant-pathogenic fungus that primarily infects cereals, such as wheat and barley, causing diseases such as spot blotch, common root rot and seedling blight. This study presents a comprehensive comparative genomic analysis of nine B. sorokiniana strains based on 16 genomic parameters, including genome completeness, virulence factors, secondary metabolite biosynthesis, effector proteins and CAZymes, to explore their genetic diversity, genome assembly quality and pathogenic potential. Genomic assemblies of the strains LK93 and ND93-1 exhibited higher N50, L50, BUSCO completeness scores and gene annotations, and were designated as high-quality. Similarly, ND90Pr and BS112 demonstrated a rich arsenal of CAZymes and effector proteins, which indicated their greater infection potential. Variability in biosynthetic gene clusters, especially the presence of isocyanide-NRPS and fungal RiPP clusters, highlights the ecological adaptability and metabolic diversity of these strains. The study also revealed distinct protein family distributions and effector protein repertoires, supporting strain-specific pathogenic strategies. Phylogenetic analyses grouped the strains into three clusters, indicating evolutionary divergence and potential ecological specialisation. The findings of the study underscore the importance of high-quality genomic data and propose LK93 and ND93-1 as more reliable reference genomes for B. sorokiniana. Integrating transcriptomics, proteomics and pathogenicity data, along with expanded strain sampling and unified assembly pipelines, can enhance understanding of the molecular basis of pathogenicity and help develop suitable disease management strategies to control this agriculturally important pathogen.
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