Understanding the Genomic Diversity and Pathogenicity of Cotton Fusarium Wilt

Fusarium wilt disease of cotton (Gossypium spp.) is caused by soil-borne fungal pathogen Fusarium oxysporum f. sp. vasinfectum (Fov). A variety of Fov genotypes appear across the Cotton Belt in the United States. The variation in symptoms expresses virulence differences with taxonomic classification and complex interaction with field environmental factors. This affects the design and conduct of cotton resistance breeding programs. The Fov race classification are mainly based on differences in virulence and partial sequence fragments. It remains unknown the phylogenic relationship of Fov genotypes at the whole genome level. In 2017, official confirmation of field sites in El Paso, Texas infested with Fov4 was made. However, it remains unknown whether Fov4 from El Paso is the same as the one from California and the field composition of Fov at the whole genome level. In this talk, I will present our recent work on the identification of the Fov field pathogen genotypes using a combination of nanopore and Illumina sequencing. We have collected 40~90 isolates from El Paso each year from 2017 to 2019, characterized their growth morphologies and virulence in cotton, and performed a preliminary phylogenetic analysis based on the sequence differences in four commonly used marker genes. We further perform the long-read whole-genome nanopore MinION sequencing coupled with Illumina sequencing to examine the genetic relationship of ~40 isolates, and California isolates CA10 (race 1) and CA14 (race 4), assembled the whole genome, and defined the accessory chromosomes. These efforts reveal the pathogen genetic identities leading to the recent outbreaks of Fov in west Texas, offer insights into whether the disease is due to Fov4 contamination and/or pathogen virulence shift, and facilitate the disease molecular detection efforts in effectively tracking the pathogen spread. In addition, I will discuss the pathogen infection process with live-cell imaging at the single-cell level.