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Bioinformatics Advance Access originally published online on January 7, 2009
Bioinformatics 2009 25(3):309-314; doi:10.1093/bioinformatics/btn632
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

PanCGH: a genotype-calling algorithm for pangenome CGH data

Jumamurat R. Bayjanov 1,*, Michiel Wels 1,2,3, Marjo Starrenburg 2,4, Johan E. T. van Hylckama Vlieg 2,3,4, Roland J. Siezen 1,2,3,4 and Douwe Molenaar 2,3,4

1Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, 2NIZO food research, P.O. Box 20, 6710 BA Ede, 3TI Food and Nutrition, P.O. Box 557, 6700 AN Wageningen and 4Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands

*To whom correspondence should be addressed.


  Abstract

Motivation: Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data.

Results: We have developed the algorithm PanCGH that incorporates orthology information about genes to predict the presence or absence of orthologous genes in a query organism using CGH arrays that target the genomes of sequenced representatives of a group of microorganisms. PanCGH was tested and applied in the analysis of genetic diversity among 39 Lactococcus lactis strains from three different subspecies (lactis.cremoris, hordniae) and isolated from two different niches (dairy and plant). Clustering of these strains using the presence/absence data of gene orthologs revealed a clear separation between different subspecies and reflected the niche of the strains.

Contact: J.Bayjanov{at}cmbi.ru.nl

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Martin Bishop

Received on September 9, 2008; revised on November 20, 2008; accepted on December 4, 2008

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