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Supervised Lowess normalization of comparative genome hybridization data--application to lactococcal strain comparisons.

ABSTRACT: BACKGROUND: Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. Since prokaryotes in general have less conserved genome sequences than eukaryotes, sequence divergences between the genes in the genomes used for an aCGH experiment obstruct determination of genome variations (e.g. deletions). Current normalization methods do not take into consideration sequence divergence between target and microarray features and therefore cannot distinguish a difference in signal due to systematic errors in the data or due to sequence divergence. RESULTS: We present supervised Lowess, or S-Lowess, an application of the subset Lowess normalization method. By using a predicted subset of array features with minimal sequence divergence between the analyzed strains for the normalization procedure we remove systematic errors from dual-dye aCGH data in two steps: (1) determination of a subset of conserved genes (i.e. likely conserved genes, LCG); and (2) using the LCG for subset Lowess normalization. Subset Lowess determines the correction factors for systematic errors in the subset of array features and normalizes all array features using these correction factors. The performance of S-Lowess was assessed on aCGH experiments in which differentially labeled genomic DNA fragments of Lactococcus lactis IL1403 and L. lactis MG1363 strains were hybridized to IL1403 DNA microarrays. Since both genomes are sequenced and gene deletions identified, the success rate of different aCGH normalization methods in detecting these deletions in the MG1363 genome were determined. S-Lowess detects 97% of the deletions, whereas other aCGH normalization methods detect up to only 60% of the deletions. CONCLUSION: S-Lowess is implemented in a user-friendly web-tool accessible from http://bioinformatics.biol.rug.nl/websoftware/s-lowess. We demonstrate that it outperforms existing normalization methods and maximizes detection of genomic variation (e.g. deletions) from microbial aCGH data.

SUBMITTER: van Hijum SA

PROVIDER: S-EPMC2275246 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Supervised Lowess normalization of comparative genome hybridization data--application to lactococcal strain comparisons.

van Hijum Sacha A F T SA Baerends Richard J S RJ Zomer Aldert L AL Karsens Harma A HA Martin-Requena Victoria V Trelles Oswaldo O Kok Jan J Kuipers Oscar P OP

BMC bioinformatics 20080211

<h4>Background</h4>Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. Since prokaryotes in general have less conserved genome sequences than eukaryotes, sequence divergences between the genes in the genomes used for an aCGH experiment obstruct determination of genome variations (e.g. deletions). Current normalization methods do not take into consideration sequence divergence between target and microarray features and theref ...[more]

PMID: 18267014

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Project description:Background Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. In aCGH data, systematic errors are comparable to those occurring in transcriptome data. However, especially for microbes, an additional source of variation exists: differences in hybridization due to gene sequence divergence between the strains hybridized. Current normalization methods do not take this source of variation into consideration. Results We present Supervised Lowess, or S-Lowess, an application of the subset Lowess normalization method that does take difference in genomic content into account. The performance of S-Lowess was assessed on aCGH experiments in which differentially labeled genomic DNA fragments of Lactococcus lactis IL1403 and L. lactis MG1363 strains were hybridized to IL1403 microarrays. Since both genome sequences are known (they have only on average 85 % sequence identity), the success rate in detecting deletions in the MG1363 genome of different aCGH normalization methods can be compared. S-Lowess detects 97% of the deletions, whereas other aCGH normalization methods detect up to only 60% of the deletions. Conclusions S-Lowess removes systematic errors from dual-dye aCGH data in two steps: (i) determination of likely homologous genes (LHG); and (ii) estimation of correction factors for systematic errors from spots of LHG and subset Lowess normalization of the remaining spots using these correction factors. It is implemented in a user-friendly web-tool accessible from http://bioinformatics.biol.rug.nl/websoftware/s-lowess. We demonstrate that it outperforms existing normalization methods and maximizes the number of detectable genomic deletions or duplications from microbial aCGH data. Keywords: comparative genome hybridisation In this study, 4 aCGH comparisons (slides) between L. lactis MG1363 and L. lactis IL1403 were performed (including dye swap with biological replicates; see also supplementary materials). The resulting aCGH slide signals were normalized using the different 'likely homologous gene' (LHG) sets (see above) yielding ratios of signals of labelled DNA of MG1363 over those of IL1403. A maximum of 8 ratios per amplicon (gene) were obtained for the 4 hybridized slides (each with 2 replicate spots per amplicon). Only genes with at least 5 measurements were used in this study. The normalization methods evaluated in this study are: a) no normalization, b) total signal normalization, c) grid-based Lowess (implemented in PreP; f = 0.7) [GarcM-CM--a de la Nava, J et al. 2003. Bioinformatics 19:2328-2329], and d) S-Lowess using different subsets of conserved lactococcal genes (for details see above). Results with the MANOR R package (spatial normalization; standard parameters) [Neuvial P, et al. 2006. BMC Bioinformatics 7:264; Liva S, et al. 2006. Nucleic Acids Res 34:W477-W481] are shown in our supplementary materials.

Project description:BACKGROUND: Many fruit-tree species, including relevant Citrus spp varieties exhibit a reproductive biology that impairs breeding and strongly constrains genetic improvements. In citrus, juvenility increases the generation time while sexual sterility, inbreeding depression and self-incompatibility prevent the production of homozygous cultivars. Genomic technology may provide citrus researchers with a new set of tools to address these various restrictions. In this work, we report a valuable genomics-based protocol for the structural analysis of deletion mutations on an heterozygous background. RESULTS: Two independent fast neutron mutants of self-incompatible clementine (Citrus clementina Hort. Ex Tan. cv. Clemenules) were the subject of the study. Both mutants, named 39B3 and 39E7, were expected to carry DNA deletions in hemizygous dosage. Array-based Comparative Genomic Hybridization (array-CGH) using a Citrus cDNA microarray allowed the identification of underrepresented genes in these two mutants. Subsequent comparison of citrus deleted genes with annotated plant genomes, especially poplar, made possible to predict the presence of a large deletion in 39B3 of about 700 kb and at least two deletions of approximately 100 and 500 kb in 39E7. The deletion in 39B3 was further characterized by PCR on available Citrus BACs, which helped us to build a partial physical map of the deletion. Among the deleted genes, ClpC-like gene coding for a putative subunit of a multifunctional chloroplastic protease involved in the regulation of chlorophyll b synthesis was directly related to the mutated phenotype since the mutant showed a reduced chlorophyll a/b ratio in green tissues. CONCLUSION: In this work, we report the use of array-CGH for the successful identification of genes included in a hemizygous deletion induced by fast neutron irradiation on Citrus clementina. The study of gene content and order into the 39B3 deletion also led to the unexpected conclusion that microsynteny and local gene colinearity in this species were higher with Populus trichocarpa than with the phylogenetically closer Arabidopsis thaliana. This work corroborates the potential of Citrus genomic resources to assist mutagenesis-based approaches for functional genetics, structural studies and comparative genomics, and hence to facilitate citrus variety improvement.

Dataset Information

Supervised Lowess normalization of comparative genome hybridization data--application to lactococcal strain comparisons.

Publications

Supervised Lowess normalization of comparative genome hybridization data--application to lactococcal strain comparisons.

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