Methodology article

RIPCAL: a tool for alignment-based analysis of repeat-induced point mutations in fungal genomic sequences

James K Hane and Richard P Oliver

Australian Centre for Necrotrophic Fungal Pathogens, Faculty of Health Sciences, Murdoch University, South Street, Murdoch, 6150, Australia

author email corresponding author email

BMC Bioinformatics 2008, 9:478doi:10.1186/1471-2105-9-478

Published:	12 November 2008

Abstract

Background

Repeat-induced point mutation (RIP) is a fungal-specific genome defence mechanism that alters the sequences of repetitive DNA, thereby inactivating coding genes. Repeated DNA sequences align between mating and meiosis and both sequences undergo C:G to T:A transitions. In most fungi these transitions preferentially affect CpA di-nucleotides thus altering the frequency of certain di-nucleotides in the affected sequences. The majority of previously published in silico analyses were limited to the comparison of ratios of pre- and post-RIP di-nucleotides in putatively RIP-affected sequences – so-called RIP indices. The analysis of RIP is significantly more informative when comparing sequence alignments of repeated sequences. There is, however, a dearth of bioinformatics tools available to the fungal research community for alignment-based RIP analysis of repeat families.

Results

We present RIPCAL http://www.sourceforge.net/projects/ripcal webcite, a software tool for the automated analysis of RIP in fungal genomic DNA repeats, which performs both RIP index and alignment-based analyses. We demonstrate the ability of RIPCAL to detect RIP within known RIP-affected sequences of Neurospora crassa and other fungi. We also predict and delineate the presence of RIP in the genome of Stagonospora nodorum – a Dothideomycete pathogen of wheat. We show that RIP has affected different members of the S. nodorum rDNA tandem repeat to different extents depending on their genomic contexts.

Conclusion

The RIPCAL alignment-based method has considerable advantages over RIP indices for the analysis of whole genomes. We demonstrate its application to the recently published genome assembly of S. nodorum.