ArticleBMC bioinformatics2008
RIPCAL: a tool for alignment-based analysis of repeat-induced point mutations in fungal genomic sequences.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
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107 citing papers in PubMed, 180 citations in OpenAlex.
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47 more citing papers are in PubMed but not listed here.
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2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRepeat-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.
resultsWe present RIPCAL http://www.sourceforge.net/projects/ripcal, 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.
conclusionThe 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.
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