Organelle rrn5 sequences discovered and validated in the course of our analyses (see below) were included in an additional CM (mtAT-5S) based on a wide taxonomic sampling and a focus on derived and A+T-rich 5S rRNAs that are less effectively identified with the basic mt-5S model. A fourth model has been developed (mtPerm-5S) based on the permuted 5S rRNAs encoded by mtDNAs from brown algae and potentially several other stramenopiles. All models will be made available (together with the seed sequence alignments) in the Rfam database. They will be also included in our automated organelle genome annotation tool MFannot (
Annotating Organelle rrn5 Genes
Organelle rrn5 sequences discovered and validated in the course of our analyses (see below) were included in an additional CM (mtAT-5S) based on a wide taxonomic sampling and a focus on derived and A+T-rich 5S rRNAs that are less effectively identified with the basic mt-5S model. A fourth model has been developed (mtPerm-5S) based on the permuted 5S rRNAs encoded by mtDNAs from brown algae and potentially several other stramenopiles. All models will be made available (together with the seed sequence alignments) in the Rfam database. They will be also included in our automated organelle genome annotation tool MFannot (
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Variable analysis
- Sequence alignment methods used (MUSCLE v3.6, RNAalifold)
- Infernal program parameters (Cmbuild, Cmcalibrate) used for building CMs
- Mitochondrial and plastid rrn5 gene sequences identified and validated
- Mitochondrion- and plastid-specific covariance models (mt-5S and pt-5S) developed
- Chondrus crispus mitochondrial rrn5 and Bryopsis hypnoides plastid rrn5 gene sequences (removed due to disputed or incorrect annotation)
- Columns in sequence alignments that are not reliably aligned (masked during CM building)
- Test set of 108 mtDNA-encoded and 500 ptDNA-encoded rrn5 genes (Supplementary Table S1) used for developing and testing CMs
- None mentioned
Annotations
Based on most similar protocols
As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.
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