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Pipeline publication

[…] eck to what degree such differences or errors in the reference genome sequences contributed to the identified putative editing sites, we analyzed how many putative editing sites occurred in the RNA-seq data from all samples with at least 95% of the variant base. This resulted in 15 sites for S. macrospora and 13 sites for P. confluens. Thus, the large majority of the hundreds to thousands of potential editing sites that were identified (see below) are not due to strain differences or errors in the genome sequences., For a comparison of editing sites of S. macrospora with P. confluens and F. graminearum, respectively, orthologs between S. macrospora and the other two fungi were identified by reciprocal BLAST as described (, ). Putative editing sites identified in wild type protoperithecial samples from S. macrospora were compared with F. graminearum editing sites found by and with putative editing sites identified in sexual tissue from P. confluens. Functional classification of genes with putative editing sites was done using FungiFun 2 () with the FunCat ontology (), or Ontologizer () based on gene ontology (GO) annotations from UniProt (, )., To verify that the observed variants are indeed editing sites and not errors in the genome sequences or RNA-seq artefacts, polymerase chain reaction (PCR) fragments from five and six genes covering 12 and 16 putative editing sites of S. macrospora and P. confluens, respectively, were amplified from genomic DNA as well as cDNA derived from samples grown under conditions for sexual development. Oligonucleotides for PCR are given in , online. PCR fragments were either sequenced directly by Sanger sequencing, or cloned into vectors pDrive (Qiagen, Hilden, Germany) or pJet12 (Thermo Fisher Scientific, Waltham, MA, USA) an […]

Pipeline specifications

Software tools RecBlast, FungiFun, Ontologizer
Databases FunCat