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Using Mahalanobis distance to compare genomic signatures between bacterial plasmids and chromosomes.

ABSTRACT: Plasmids are ubiquitous mobile elements that serve as a pool of many host beneficial traits such as antibiotic resistance in bacterial communities. To understand the importance of plasmids in horizontal gene transfer, we need to gain insight into the 'evolutionary history' of these plasmids, i.e. the range of hosts in which they have evolved. Since extensive data support the proposal that foreign DNA acquires the host's nucleotide composition during long-term residence, comparison of nucleotide composition of plasmids and chromosomes could shed light on a plasmid's evolutionary history. The average absolute dinucleotide relative abundance difference, termed delta-distance, has been commonly used to measure differences in dinucleotide composition, or 'genomic signature', between bacterial chromosomes and plasmids. Here, we introduce the Mahalanobis distance, which takes into account the variance-covariance structure of the chromosome signatures. We demonstrate that the Mahalanobis distance is better than the delta-distance at measuring genomic signature differences between plasmids and chromosomes of potential hosts. We illustrate the usefulness of this metric for proposing candidate long-term hosts for plasmids, focusing on the virulence plasmids pXO1 from Bacillus anthracis, and pO157 from Escherichia coli O157:H7, as well as the broad host range multi-drug resistance plasmid pB10 from an unknown host.

SUBMITTER: Suzuki H

PROVIDER: S-EPMC2602791 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

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Using Mahalanobis distance to compare genomic signatures between bacterial plasmids and chromosomes.

Suzuki Haruo H Sota Masahiro M Brown Celeste J CJ Top Eva M EM

Nucleic acids research 20081025 22

Plasmids are ubiquitous mobile elements that serve as a pool of many host beneficial traits such as antibiotic resistance in bacterial communities. To understand the importance of plasmids in horizontal gene transfer, we need to gain insight into the 'evolutionary history' of these plasmids, i.e. the range of hosts in which they have evolved. Since extensive data support the proposal that foreign DNA acquires the host's nucleotide composition during long-term residence, comparison of nucleotide ...[more]

PMID: 18953039

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Project description:Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly et al. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE.

Dataset Information

Using Mahalanobis distance to compare genomic signatures between bacterial plasmids and chromosomes.

Publications

Using Mahalanobis distance to compare genomic signatures between bacterial plasmids and chromosomes.

Similar Datasets

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