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Selecting representative model micro-organisms

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journal contribution
posted on 2023-05-17, 02:21 authored by Barbara HollandBarbara Holland, Schmid, J
Background Micro-biological research relies on the use of model organisms that act as representatives of their species or subspecies, these are frequently well-characterized laboratory strains. However, it has often become apparent that the model strain initially chosen does not represent important features of the species. For micro-organisms, the diversity of their genomes is such that even the best possible choice of initial strain for sequencing may not assure that the genome obtained adequately represents the species. To acquire information about a species' genome as efficiently as possible, we require a method to choose strains for analysis on the basis of how well they represent the species. Results We develop the Best Total Coverage (BTC) method for selecting one or more representative model organisms from a group of interest, given that rough genetic distances between the members of the group are known. Software implementing a "greedy" version of the method can be used with large data sets, its effectiveness is tested using both constructed and biological data sets. Conclusion In both the simulated and biological examples the greedy-BTC method outperformed random selection of model organisms, and for two biological examples it outperformed selection of model strains based on phylogenetic structure. Although the method was designed with microbial species in mind, and is tested here on three microbial data sets, it will also be applicable to other types of organism.


Publication title

BMC Microbiology










School of Natural Sciences


Biomed Central Ltd

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236 Grays Inn Road, Floor 6, London, England, WC1X

Rights statement

© 2005 Holland and Schmid; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Open

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Expanding knowledge in the biological sciences

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