Speakers: Sanzhen Liu, PhD

Sanzhen Liu, PhD

Professor in the Department of Plant Pathology
Kansas State University


Dr. Sanzhen Liu holds BS and MS degrees from Xiamen University and completed his PhD and postdoctoral research at Iowa State University. Currently, he serves as a Professor in the Department of Plant Pathology at Kansas State University. He chairs the Admission Committee of the Interdepartmental Genetics program at Kansas State University. His research primarily focuses on genetics, genomics, and computational approaches applied to maize, wheat, and their associated pathogens. Dr. Liu has developed valuable experimental tools and computational pipelines for genetic and genomic analyses. Dr. Liu has published over 90 peer-reviewed papers, featured in prestigious journals like the Plant Cell, Nature Communications, Genome Biology, and PLoS Genetics. His research has garnered over 8,000 citations. Dr. Liu has also received an early career award from the US NSF Plant Genome Research Program. His research is supported by the NSF, USDA, DOE, and Corteva Agriscience in the US.


Decoding Genomes of a Wheat Blast Pathogen

Genetic and genomic exploration of plant pathogens provides valuable insights into pathogen evolution, their ability to infect plant hosts, and the movement of diseases locally and globally. This talk will introduce a genomic analysis of the pathogen responsible for the emerging wheat blast disease, which poses a significant threat to global wheat production. Genomic data from fungal pathogens reveal highly dynamic genomes among different fungal individuals, with many, though not all, carrying a distinctive small extra chromosome known as a mini-chromosome. This mini-chromosome appears to enhance aggressiveness and plays a role in pathogen adaptation. One fungal strain, possessing this mini-chromosome, has become a pandemic strain, infecting wheat across multiple continents. The study of wheat blast pathogens utilizes traditional microscopic techniques, molecular tools, state-of-the-art genome sequencing technology, and computational approaches, including artificial intelligence (AI). In the genomic field, data often reach gigabyte and terabyte scales, underscoring the importance of computational biology for handling such large-scale datasets. Looking ahead, the application of AI promises to further unravel the genomes of various species of interest.