Current Status and Future Perspectives of Genomics Research in the Rust Fungi

• Published in: International journal of molecular sciences Vol. 23; no. 17; p. 9629
• Main Authors: Xia, Chongjing, Qiu, Age, Wang, Meinan, Liu, Taiguo, Chen, Wanquan, Chen, Xianming
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 25.08.2022; MDPI
• Subjects: Basidiomycota - genetics; Biological evolution; Biology; Chromosome Mapping; Coffee; Crop diseases; Crops; DNA methylation; effector; Evolution; Fungi; Fungi - genetics; Genes; Genomes; Genomics; Hypotheses; Pathogens; Plant diseases; Plant Diseases - genetics; Plant Diseases - microbiology; Population dynamics; Pucciniales; Review; Rust fungi; rust fungus; secreted protein; Virulence; Virulence - genetics; Wheat; whole-genome sequencing; genomics; effector; rust fungus; evolution; whole-genome sequencing; secreted protein
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms23179629

Rust fungi in Pucciniales have caused destructive plant epidemics, have become more aggressive with new virulence, rapidly adapt to new environments, and continually threaten global agriculture. With the rapid advancement of genome sequencing technologies and data analysis tools, genomics research on many of the devastating rust fungi has generated unprecedented insights into various aspects of rust biology. In this review, we first present a summary of the main findings in the genomics of rust fungi related to variations in genome size and gene composition between and within species. Then we show how the genomics of rust fungi has promoted our understanding of the pathogen virulence and population dynamics. Even with great progress, many questions still need to be answered. Therefore, we introduce important perspectives with emphasis on the genome evolution and host adaptation of rust fungi. We believe that the comparative genomics and population genomics of rust fungi will provide a further understanding of the rapid evolution of virulence and will contribute to monitoring the population dynamics for disease management.