Genetic Diversity and Classification of Colletotrichum sublineola Pathotypes Using a Standard Set of Sorghum Differentials.
Louis K PromEzekiel Jin Sung AhnRamasamy PerumalHugo E CuevasWilliam L RooneyThomas S IsakeitClint W MagillPublished in: Journal of fungi (Basel, Switzerland) (2023)
Anthracnose, incited by Colletotrichum sublineola, is the most destructive foliar disease of sorghum and, under severe conditions, yield losses can exceed 80% on susceptible cultivars. The hyper-variable nature of the pathogen makes its management challenging despite the occurrence of several resistant sources. In this study, the genetic variability and pathogenicity of 140 isolates of C. sublineola, which were sequenced using restriction site-associated sequencing (RAD-Seq), resulted in 1244 quality SNPs. The genetic relationship based on the SNP data showed low to high genetic diversity based on isolates' origin. Isolates from Georgia and North Carolina were grouped into multiple clusters with some level of genetic relationships to each other. Even though some isolates from Texas formed a cluster, others clustered with isolates from Puerto Rico. The isolates from Puerto Rico showed scattered distribution, indicating the diverse nature of these isolates. A population structure and cluster analysis revealed that the genetic variation was stratified into eight populations and one admixture group. The virulence pattern of 30 sequenced isolates on 18 sorghum differential lines revealed 27 new pathotypes. SC748-5, SC112-14, and Brandes were resistant to all the tested isolates, while BTx623 was susceptible to all. Line TAM428 was susceptible to all the pathotypes, except for pathotype 26. Future use of the 18 differentials employed in this study, which contains cultivars/lines which have been used in the Americas, Asia, and Africa, could allow for better characterization of C. sublineola pathotypes at a global level, thus accelerating the development of sorghum lines with stable resistance to the anthracnose pathogen.
Keyphrases
- genetic diversity
- genome wide
- single cell
- escherichia coli
- staphylococcus aureus
- machine learning
- dna damage
- copy number
- pseudomonas aeruginosa
- candida albicans
- dna methylation
- gene expression
- rna seq
- biofilm formation
- drinking water
- electronic health record
- big data
- dna repair
- oxidative stress
- tertiary care
- drug induced
- current status