1a.Objectives (from AD-416):
The objective of this cooperative research project is to find the difference of
genome organization between Aspergillus flavus and A. oryzae.
1b.Approach (from AD-416):
Comparison of the genes existing in each genome by sequence similarity and/or by
comparative genomic hybridization (CGH).
In collaboration with Southern Regional Research Center (SRRC), Aspergillus flavus whole genome (the entire genetic component of the organism) sequence was used for the comparison with Aspergillus oryzae genome sequence at Advanced Industrial Science & Technology (AIST), Japan. This comparison between the two Aspergillus species resulted in the identification of hundreds of genes that may be unique to Aspergillus flavus and unique to Aspergillus oryzae as well as a vast majority that were found to be common in both. Analysis revealed that there are fewer unique genes in each genome than we had anticipated. Only about 300 or so genes uniquely present in each species contribute to the aflatoxin-producing ability in Aspergillus flavus and non-toxigenicity in Aspergillus oryzae. The two species share over 95% sequenced similarity at deoxyribonucleic acid (DNA) level. An even higher conservation was identified in specific and critical regions of gene sequences. Efforts have been made to identify the genome structure and gene distribution within similar regions. Further, we have compared the potential secondary metabolism (processes not required for growth) gene clusters in both species to assign functions to the clusters for the secondary metabolites that these genes would be responsible for producing. These secondary metabolites could be mycotoxins or potentially be of pharmaceutical applications. This comparative genomics project will significantly promote and speed up the process of detecting genes governing or related to aflatoxin formation, as well as fungal survival in the field. Eventually we will identify factors in the fungus that could be targeted for controlling aflatoxin contamination through plant breeding or genetic engineering of commercial crops. Progress has been made in developing a model that can predict and identify potential secondary metabolism clusters in the genome in collaboration with ARS/SRRC. This model is to use gene expression data generated by either of two techniques namely microarray experiments or ribonucleic acid (RNA)-Seq.