Euglenids (Euglenozoa) contain several forms of extrachromosomal DNA (ecDNA) in their cells, including the ribosomal DNA operon (rDNA), the mitochondrial genome (mtDNA), and, in photosynthetic species, the plastid genome (ptDNA). These ecDNA elements can be easily and accurately assembled and annotated even from limited sequencing data, such as single-cell genomic or metagenomic datasets. They are an important source of information for phylogenomic analyses, metabarcoding and evolutionary studies. In this chapter, we present a robust and adaptable bioinformatics pipeline for the identification, assembly, and annotation of extrachromosomal DNA from whole-genome datasets. The pipeline was developed with euglenids in mind and takes into account their unique genomic features, but can also be adapted for other Euglenozoa (and protists). This approach enables the recovery of organellar and rDNA sequences with high confidence and supports both targeted studies and large-scale environmental analyses.

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Euglenid Extrachromosomal DNA: Assembly and Annotation

  • Paweł Hałakuc,
  • Kacper Maciszewski,
  • Anna Karnkowska

摘要

Euglenids (Euglenozoa) contain several forms of extrachromosomal DNA (ecDNA) in their cells, including the ribosomal DNA operon (rDNA), the mitochondrial genome (mtDNA), and, in photosynthetic species, the plastid genome (ptDNA). These ecDNA elements can be easily and accurately assembled and annotated even from limited sequencing data, such as single-cell genomic or metagenomic datasets. They are an important source of information for phylogenomic analyses, metabarcoding and evolutionary studies. In this chapter, we present a robust and adaptable bioinformatics pipeline for the identification, assembly, and annotation of extrachromosomal DNA from whole-genome datasets. The pipeline was developed with euglenids in mind and takes into account their unique genomic features, but can also be adapted for other Euglenozoa (and protists). This approach enables the recovery of organellar and rDNA sequences with high confidence and supports both targeted studies and large-scale environmental analyses.