Submitted to: Mycological International Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: April 1, 2006
Publication Date: August 20, 2006
Citation: Butchko, R.A., Brown, D.W., Proctor, R. 2006. Fumonisin mycotoxin biosynthesis, genetics and genomics in fusarium verticillioides [abstract]. 8th International Mycological Congress. p. 266. Technical Abstract: Fusarium verticillioides is the causal agent of seedling disease, stalk rot and ear rot of maize and can produce the mycotoxins fumonisins. Fumonisins are polyketide derived molecules synthesized through a multi-step biosynthetic pathway by enzymes encoded by a coregulated cluster of genes on chromosome I. Fumonisins are toxic to both humans and animals and have most recently been described as teratogenic, causing neural tube defects in mice. In an effort to reduce or eliminate fumonisin contamination of maize, we are employing genomic resources to elucidate the genetic regulation of fumonisin production. Genomic resources have recently become available for F. verticillioides and include libraries of expressed sequence tags (ESTs), microarrays and whole genome sequence. In conjunction with The Institute for Genomic Research (TIGR), we have constructed a dense EST library representing as many as 11,000 unique genes in F. verticillioides. This EST library has been utilized to create microarray chips containing oligonucleotide probes for all unique sequences identified from the libraries. Comparison of ESTs generated from different culture conditions has allowed us to identify differentially expressed genes with potential roles in regulating fumonisin biosynthesis. Detailed analysis of ESTs from different culture conditions has revealed previously unidentified genes in the fumonisin biosynthetic gene cluster. In 2005, a 4X coverage of the Fusarium verticillioides genome generated at Syngenta and assembled at the Broad Institute was made publicly available. The intersection of whole genome sequence, EST libraries and microarrays is allowing us to more comprehensively define genes and describe their expression at the transcription level. We have combined whole genome sequence to determine the physical location of genes identified from EST analysis with expression data determined from microarray analysis which has allowed us to categorize genes spatially in the genome and their expression temporally.