Background: Identifying pathogen virulence genes required to cause disease is crucial to understand the mechanisms underlying the pathogenic process. Plasmid insertion mutagenesis of fungal protoplasts is frequently used for this purpose in filamentous ascomycetes. Post transformation, the mutant population is screened for loss of virulence to a specific plant or animal host. Identifying the insertion event has previously met with varying degrees of success, from a cleanly disrupted gene with minimal deletion of nucleotides at the insertion point to multiple-copy insertion events and large deletions of chromosomal regions. Currently, extensive mutant collections exist in laboratories globally where it was hitherto impossible to identify all the affected genes.
Results: We used a whole-genome sequencing (WGS) approach using Illumina HiSeq 2000 technology to investigate DNA tag insertion points and chromosomal deletion events in mutagenised, reduced virulence F. graminearum isolates identified in disease tests on wheat (Triticum aestivum). We developed the FindInsertSeq workflow to localise the DNA tag insertions to the nucleotide level. The workflow was tested using four mutants showing evidence of single and multi-copy insertions in DNA blot analysis. FindInsertSeq was able to identify both single and multi-copy concatenation insertion sites. By comparing sequencing coverage, unexpected molecular recombination events such as large tagged and untagged chromosomal deletions, and DNA amplification were observed in three of the analysed mutants. A random data sampling approach revealed the minimum genome coverage required to survey the F. graminearum genome for alterations.
Conclusions: This study demonstrates that whole-genome re-sequencing to 22x fold genome coverage is an efficient tool to characterise single and multi-copy insertion mutants in the filamentous ascomycete Fusarium graminearum. In some cases insertion events are accompanied with large untagged chromosomal deletions while in other cases a straight-forward insertion event could be confirmed. The FindInsertSeq analysis workflow presented in this study enables researchers to efficiently characterise insertion and deletion mutants.