Powered by Precision, Driven by Quality

Overall genome relatedness index (OGRI)

Subscribe To Our Newsletter

Get updates and learn from the best

Overall genome relatedness index (OGRI) is a term first coined by Chun & Rainey (2014) and represents any measurements indicating how similar two genome sequences are. There are many algorithms to calculate OGRI values, but the most widely used algorithm for taxonomic studies is Average Nucleotide Identity (ANI). The original ANI algorithm was first introduced and refined by Jim Teidje’s group (Konstantinidis et al. 2005; Goris et al. 2007). Since then, as more genome sequences are accumulated in public databases, ANI has been widely used in the description of novel species and, less frequently, for the identification of newly isolated strains (as genome sequencing is still expensive for routine identification).

Even though the algorithm for ANI calculation is clear, its implementation as a software can be different. Different ANI values can be obtained by different software tools as reported by Figueras et al. (2015). Actually, this is a general problem in bioinformatics; different computer programs using the same algorithm may produce different results. This is particularly problematic when web-service is used since web-service cannot be replicated with confidence in future.

OrthoANI is a modified algorithm of the original ANI and has advantages over the original ANI [Learn more about OrthoANI]. We recommend OrthoANIu (with usearch program) for taxonomic purposes. Web-service is available here and standalone software can be downloaded from here.

Last updated on Sept 16, 2017 (JC)

References

  1. Chun, J. & Rainey, F.A. Integrating genomics into the taxonomy and systematics of the Bacteria and Archaea. Int J Syst Evol Microbiol 64, 316-24 (2014).
  2. Konstantinidis, K.T. & Tiedje, J.M. Genomic insights that advance the species definition for prokaryotes. Proc Natl Acad Sci U S A 102, 2567-72 (2005).
  3. Goris, J. et al. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 57, 81-91 (2007).
  4. Figueras, M.J., Beaz-Hidalgo, R., Hossain, M.J. & Liles, M.R. Taxonomic affiliation of new genomes should be verified using average nucleotide identity and multilocus phylogenetic analysis. Genome Announc 2(6) (2014).
  5. Lee, I., Kim, Y.O., Park, S.C. & Chun, J. OrthoANI: An improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol Microbiol 66: 1100-1103 (2015).

Subscribe To Our Newsletter

Get updates and learn from the best

More To Explore

Genome annotation

The analysis of all bacterial genome starts with genome annotation.  This process can be divided into two steps: Gene-finding step and Functional Annotation step. “Gene-finding”

Gene frequency plot in pan-genome

All potential orthologous protein-coding  genes (=CDSs) are clustered into non-redundant gene sets after pan-genome calculation to generate “Pan-genome Orthologous Groups (POGs)”. Obviously, a core part

Share This Post

Share on facebook
Share on linkedin
Share on twitter
Share on email
small_c_popup.png

Have a Question? Let's have a chat?

We're here to answer any question you might have

small_c_popup.png

Have a Question? Let's have a chat?

We're here to answer any question you might have

small_c_popup.png

Stay up to date

Keep up with our latest developments